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[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n/\n/\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE event (\n\t\"Event_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\t\"Event_Attendance\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 4, 3\nDate : 9 April 2014, 7 October 2010, 11 October 2007, 13 October 2008, 20 June 2018\nVenue : Motagua, Platense, Hispano, Victoria, Marathon\nName : Global Awarding, Public Debating, Special Exhibition, Government Hearing, Olympia Games Openning\nEvent_Attendance : 369, 1675, 2356, 6650, 225\n/\n \nCREATE TABLE \"Roles\" (\n\t\"Role_Code\" CHAR(15) NOT NULL, \n\t\"Role_Name\" VARCHAR(255), \n\t\"Role_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Role_Code\")\n)\n/\nColumns in Roles and all categories for low cardinality columns :\nRole_Code : PR, HR, PT, MG, ED\nRole_Name : Proof Reader, Human Resource, Editor, Photo, Manager\nRole_Description : Itaque dolor ut nemo rerum vitae provident. Vel laborum ipsum velit sint. Et est omnis dignissimos., Ut sed quae eaque mollitia qui hic. Natus ea expedita et odio illum fugiat qui natus. Consequatur velit ut dolorem cum ullam esse deserunt dignissimos. Enim non non rem officiis quis., Aut modi nihil molestias temporibus sit rerum. Sit neque eaque odio omnis incidunt., Vero harum corrupti odit ipsa vero et odio. Iste et recusandae temporibus maxime. Magni aspernatur fugit quis explicabo totam esse corrupti., Et totam est quibusdam aspernatur ut. Vitae perferendis eligendi voluptatem molestiae rem ut enim. Ipsum expedita quae earum unde est. Repellendus ut ipsam nihil accusantium sit. Magni accusantium numquam quod et.\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n/\n/\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n" }, { "role": "user", "content": "What are the ids of the students who either registered or attended a course?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: student_course_registrations, student_course_attendance.\nFrom these tables, I'll be using the following columns: student_id.\nThe SQL query I'll be generating is:\nSELECT student_id FROM student_course_registrations UNION SELECT student_id FROM student_course_attendance" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE device (\n\t\"Device_ID\" INTEGER, \n\t\"Device\" TEXT, \n\t\"Carrier\" TEXT, \n\t\"Package_Version\" TEXT, \n\t\"Applications\" TEXT, \n\t\"Software_Platform\" TEXT, \n\tPRIMARY KEY (\"Device_ID\")\n)\n/\nColumns in device and all categories for low cardinality columns :\nDevice_ID : 1, 2, 5, 4, 6, 3\nDevice : Huawei, Galaxy, Apple, Xiaomi, BlackBerry Storm 9530, Samsung\nCarrier : MTS Mobility, Bell Mobility, Telus Mobility, Vodafone AU, Verizon Wireless, Iusacell\nPackage_Version : 4.7.0.208, 5.0.0.742, 5.0.0.808, 5.0.0.328, 5.0.0.419\nApplications : 4.7.0.151, 5.0.0.451, 5.0.0.328, 5.0.0.419\nSoftware_Platform : iOS, Android\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"Sales\" (\n\tsales_transaction_id INTEGER, \n\tsales_details VARCHAR(255), \n\tPRIMARY KEY (sales_transaction_id), \n\tFOREIGN KEY(sales_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/\nColumns in Sales and 3 examples in each column for high cardinality columns :\nsales_transaction_id : 1, 13, 11\n/\n/\nColumns in Sales and all categories for low cardinality columns :\nsales_details : t, f, s, e, y, n, x, p, o, a\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Album\" (\n\t\"AlbumId\" INTEGER NOT NULL, \n\t\"Title\" VARCHAR(160) NOT NULL, \n\t\"ArtistId\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"AlbumId\"), \n\tFOREIGN KEY(\"ArtistId\") REFERENCES \"Artist\" (\"ArtistId\")\n)\n/\nColumns in Album and 3 examples in each column for high cardinality columns :\nAlbumId : 87, 56, 65\nTitle : The Number of The Beast, One By One, Dance Of Death\nArtistId : 87, 56, 95\n/\n\n \nCREATE TABLE actor (\n\tactor_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(45) NOT NULL, \n\tlast_name VARCHAR(45) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (actor_id)\n)\n/\nColumns in actor and 3 examples in each column for high cardinality columns :\nactor_id : 87, 56, 65\nfirst_name : WALTER, KIM, REESE\nlast_name : WITHERSPOON, OLIVIER, ALLEN\n/\n/\nColumns in actor and all categories for low cardinality columns :\nlast_update : 2006-02-15 04:34:33\n/\n" }, { "role": "user", "content": "Find the id of courses which are registered or attended by student whose id is 121?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: student_course_registrations, student_course_attendance.\nFrom these tables, I'll be using the following columns: course_id, student_id.\nThe SQL query I'll be generating is:\nSELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n/\n/\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE climber (\n\t\"Climber_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Time\" TEXT, \n\t\"Points\" REAL, \n\t\"Mountain_ID\" INTEGER, \n\tPRIMARY KEY (\"Climber_ID\"), \n\tFOREIGN KEY(\"Mountain_ID\") REFERENCES mountain (\"Mountain_ID\")\n)\n/\nColumns in climber and all categories for low cardinality columns :\nClimber_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Hans Luthringhauser, Charlie Freedman, Georg Auerbacher, Klaus Enders, Arseneus Butscher, Horst Owesle, Jean Claude Castella, Mick Horsepole, Siegfried Schauzu, L Currie\nCountry : West Germany, Switzerland, United Kingdom\nTime : 1:17.22.0, 1:25.02.8, 1:25.40.6, 1:27.28.8, 1:13.05.6, 1:18.14.6, 1:21.35.6, 1:17.16.0, 1:16.58.0, 1:14.56.4\nPoints : 8.0, 3.0, 12.0, 15.0, 10.0, 1.0, 6.0, 2.0, 4.0, 5.0\nMountain_ID : 1, 2, 5, 7, 3\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE flight (\n\tflno NUMERIC(4, 0), \n\torigin TEXT(20), \n\tdestination TEXT(20), \n\tdistance NUMERIC(6, 0), \n\tdeparture_date DATE, \n\tarrival_date DATE, \n\tprice NUMERIC(7, 2), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (flno), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid)\n) \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE job_history (\n\t\"EMPLOYEE_ID\" DECIMAL(6, 0) NOT NULL, \n\t\"START_DATE\" DATE NOT NULL, \n\t\"END_DATE\" DATE NOT NULL, \n\t\"JOB_ID\" VARCHAR(10) NOT NULL, \n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"EMPLOYEE_ID\", \"START_DATE\"), \n\tFOREIGN KEY(\"EMPLOYEE_ID\") REFERENCES employees (\"EMPLOYEE_ID\"), \n\tFOREIGN KEY(\"DEPARTMENT_ID\") REFERENCES departments (\"DEPARTMENT_ID\"), \n\tFOREIGN KEY(\"JOB_ID\") REFERENCES jobs (\"JOB_ID\")\n) \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n" }, { "role": "user", "content": "What are the ids of the courses that are registered or attended by the student whose id is 121?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: student_course_registrations, student_course_attendance.\nFrom these tables, I'll be using the following columns: course_id, student_id.\nThe SQL query I'll be generating is:\nSELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE pilot (\n\t\"Pilot_Id\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(50) NOT NULL, \n\t\"Age\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Pilot_Id\")\n)\n/\nColumns in pilot and 3 examples in each column for high cardinality columns :\nPilot_Id : 1, 11, 2\nName : Winnifred Boyle, Mr. Cristian Halvorson II, Katheryn Gorczany IV\n/\n/\nColumns in pilot and all categories for low cardinality columns :\nAge : 26, 37, 20, 25, 33, 30, 23, 29, 31\n/\n \nCREATE TABLE degrees (\n\t\"Year\" INTEGER, \n\t\"Campus\" INTEGER, \n\t\"Degrees\" INTEGER, \n\tPRIMARY KEY (\"Year\", \"Campus\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in degrees and 3 examples in each column for high cardinality columns :\nYear : 2004, 1992, 1993\nCampus : 1, 13, 11\nDegrees : 2719, 4232, 2735\n/\n\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\ttown_city VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 90928 Garret Mall, 25518 Ortiz Centers, 3986 Bergstrom Stravenue\ntown_city : Robertsberg, East Clair, Dangelohaven\nzip_postcode : 250, 193, 021\nstate_province_county : Pennsylvania, Michigan, NewHampshire\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE follows (\n\tf1 INTEGER NOT NULL, \n\tf2 INTEGER NOT NULL, \n\tPRIMARY KEY (f1, f2), \n\tFOREIGN KEY(f2) REFERENCES user_profiles (uid), \n\tFOREIGN KEY(f1) REFERENCES user_profiles (uid)\n)\n/\nColumns in follows and all categories for low cardinality columns :\nf1 : 1, 2, 5, 7, 3\nf2 : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n/\n/\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_quantity VARCHAR(15), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Order_Items and all categories for low cardinality columns :\norder_id : 13, 11, 2, 5, 7, 8, 14, 10\nproduct_id : 1, 2, 3\norder_quantity : 1, 2, 5, 7, 8, 6, 9\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Sponsor_name\" TEXT, \n\t\"Player_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Residence\" TEXT, \n\t\"Occupation\" TEXT, \n\t\"Votes\" INTEGER, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Player_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nSponsor_name : Elmwood—Transcona, Brandon—Souris, Winnipeg South Centre\nPlayer_name : Mohamed Alli, Matt Schaubroeck, Jean Luc Bouché\nOccupation : Parliamentarian, Distribution Centre Associate, Product Consultant - MLCC\nVotes : 4673, 14097, 7190\n/\n/\nColumns in player and all categories for low cardinality columns :\nGender : F, M\nResidence : Selkirk, Thompson, Brandon, Birtle, Oakbank, Winnipeg\nRank : 4th, 3rd, 2nd, 1st\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n" }, { "role": "user", "content": "What are all info of students who registered courses but not attended courses?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: student_course_registrations, student_course_attendance.\nFrom these tables, I'll be using the following columns: , student_id.\nThe SQL query I'll be generating is:\nSELECT FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"All_Documents\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Date_Stored\" DATETIME, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Name\" CHAR(255), \n\t\"Document_Description\" CHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Document_Type_Code\") REFERENCES \"Ref_Document_Types\" (\"Document_Type_Code\"), \n\tFOREIGN KEY(\"Date_Stored\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\")\n)\n/\nColumns in All_Documents and 3 examples in each column for high cardinality columns :\nDocument_ID : 120, 230, 11\nDocument_Name : Cats and me, Alan CV, Hua Mulan\n/\n/\nColumns in All_Documents and all categories for low cardinality columns :\nDate_Stored : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 1995-01-01 03:52:11, 2008-06-08 12:45:38\nDocument_Type_Code : RV, BK, PR, CV\nDocument_Description : None\nOther_Details : None\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tpayment_method VARCHAR(15) NOT NULL, \n\tcustomer_name VARCHAR(80), \n\tcustomer_phone VARCHAR(80), \n\tcustomer_email VARCHAR(80), \n\tcustomer_address VARCHAR(255), \n\tcustomer_login VARCHAR(80), \n\tcustomer_password VARCHAR(10), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : Kyle, Ruthie, Elvera\ncustomer_phone : 698-327-5792, +66(7)1491041398, 203-036-0511x96487\ncustomer_email : kristina85@example.org, davis.rosamond@example.net, marc.schiller@example.com\ncustomer_address : 80569 Crona Path Suite 165, 5514 Ophelia Cliffs Apt. 266, 56955 Desmond Lake Apt. 120\ncustomer_password : 9dc50bc5b6, f64f0fd096, 0b9f651030\n/\n/\nColumns in Customers and all categories for low cardinality columns :\npayment_method : Credit Card, Direct Debit\ncustomer_login : None\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n" }, { "role": "user", "content": "What are all details of the students who registered but did not attend any course?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: student_course_registrations, student_course_attendance.\nFrom these tables, I'll be using the following columns: , student_id.\nThe SQL query I'll be generating is:\nSELECT FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE appellations (\n\t\"No\" INTEGER, \n\t\"Appelation\" TEXT, \n\t\"County\" TEXT, \n\t\"State\" TEXT, \n\t\"Area\" TEXT, \n\t\"isAVA\" TEXT, \n\tPRIMARY KEY (\"No\"), \n\tUNIQUE (\"Appelation\")\n)\n/\nColumns in appellations and 3 examples in each column for high cardinality columns :\nNo : 53, 56, 49\nAppelation : Anderson Valley, Fiddletown, Mendocino County\nCounty : Monterey, Solano, Santa Barbara\n/\n/\nColumns in appellations and all categories for low cardinality columns :\nState : California\nArea : Sierra Foothills, Central Valley, North Coast, Central Coast, N/A, California, Santa Cruz Mountains\nisAVA : Yes, No\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Studio\" TEXT, \n\t\"Director\" TEXT, \n\t\"Gross_in_dollar\" INTEGER, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and 3 examples in each column for high cardinality columns :\nFilm_ID : 1, 13, 11\nTitle : Annie, Rocky III, Tootsie\nDirector : Richard Attenborough, Nicholas Meyer, Ted Kotcheff\nGross_in_dollar : 53977250, 76606280, 125049125\n/\n/\nColumns in film and all categories for low cardinality columns :\nStudio : MGM, United Artists, Universal, 20th Century Fox, Columbia, Paramount, Columbia / Rastar, Paramount / Lorimar, Orion / Carolco, Universal / RKO\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n/\n/\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n" }, { "role": "user", "content": "List the id of students who registered course statistics in the order of registration date." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: courses, student_course_registrations.\nFrom these tables, I'll be using the following columns: student_course_registrations.student_id, courses.course_id, student_course_registrations.course_id, courses.course_name, statistics, student_course_registrations.registration_date.\nThe SQL query I'll be generating is:\nSELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = \"statistics\" ORDER BY T2.registration_date" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Regular_Orders\" (\n\tregular_order_id INTEGER, \n\tdistributer_id INTEGER NOT NULL, \n\tPRIMARY KEY (regular_order_id), \n\tFOREIGN KEY(distributer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Regular_Orders and 3 examples in each column for high cardinality columns :\nregular_order_id : 1, 13, 11\n/\n/\nColumns in Regular_Orders and all categories for low cardinality columns :\ndistributer_id : 1, 10, 2, 7, 8, 6, 12, 3, 14, 15\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n/\n \nCREATE TABLE \"Projects\" (\n\t\"Code\" CHAR(4), \n\t\"Name\" CHAR(50) NOT NULL, \n\t\"Hours\" INTEGER, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Projects and 3 examples in each column for high cardinality columns :\nCode : Bte2, AeH6, Ast3\nName : Aerodynamics of Air Hockey, Winds: Studying Bernoullis Principle, Aerodynamics and Gas Mileage\nHours : 321, 189, 89\n/\n\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE competition_result (\n\t\"Competition_ID\" INTEGER, \n\t\"Club_ID_1\" INTEGER, \n\t\"Club_ID_2\" INTEGER, \n\t\"Score\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\", \"Club_ID_1\", \"Club_ID_2\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES competition (\"Competition_ID\"), \n\tFOREIGN KEY(\"Club_ID_2\") REFERENCES club (\"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID_1\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in competition_result and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 10\nClub_ID_1 : 1, 4, 3\nClub_ID_2 : 2, 4, 6\nScore : 11:10, 10:11, 10:3, 13:10, 12:9, 25:2\n/\n" }, { "role": "user", "content": "What are the ids of the students who registered course statistics by order of registration date?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: courses, student_course_registrations.\nFrom these tables, I'll be using the following columns: student_course_registrations.student_id, courses.course_id, student_course_registrations.course_id, courses.course_name, statistics, student_course_registrations.registration_date.\nThe SQL query I'll be generating is:\nSELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = \"statistics\" ORDER BY T2.registration_date" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n/\n \nCREATE TABLE \"Theme_Parks\" (\n\t\"Theme_Park_ID\" INTEGER NOT NULL, \n\t\"Theme_Park_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Theme_Park_ID\"), \n\tFOREIGN KEY(\"Theme_Park_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Theme_Parks and all categories for low cardinality columns :\nTheme_Park_ID : 6523, 5265, 6476\nTheme_Park_Details : Sea World, Universal Studios, Disney\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE artwork (\n\t\"Artwork_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\")\n)\n/\nColumns in artwork and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nType : Presenter Talent Show, Program Talent Show, Presenter Music/Variety Show, Program Music/Variety Show\nName : Why, I Know, Martin, Indonesian Idol, Loving you, Daniel Mananta, Back Home, Cats, Boys\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Document_Sections\" (\n\tsection_id INTEGER, \n\tdocument_code VARCHAR(15) NOT NULL, \n\tsection_sequence INTEGER, \n\tsection_code VARCHAR(20), \n\tsection_title VARCHAR(80), \n\tPRIMARY KEY (section_id), \n\tFOREIGN KEY(document_code) REFERENCES \"Documents\" (document_code)\n)\n/\nColumns in Document_Sections and 3 examples in each column for high cardinality columns :\nsection_id : 89, 62, 38\ndocument_code : 714, 217, 566\nsection_sequence : 5552, 4433, 8805\nsection_code : 91, 16, 38\n/\n/\nColumns in Document_Sections and all categories for low cardinality columns :\nsection_title : after, before\n/\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n/\n \nCREATE TABLE \"Guests\" (\n\tguest_id INTEGER NOT NULL, \n\tgender_code CHAR(1), \n\tguest_first_name VARCHAR(80), \n\tguest_last_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tPRIMARY KEY (guest_id), \n\tUNIQUE (guest_id)\n)\n/\nColumns in Guests and 3 examples in each column for high cardinality columns :\nguest_id : 1, 13, 11\nguest_first_name : Louvenia, Lou, Keith\nguest_last_name : Bode, Mante, Schowalter\ndate_of_birth : 2001-06-18 20:05:55, 1980-06-20 18:15:39, 1997-01-15 17:37:40\n/\n/\nColumns in Guests and all categories for low cardinality columns :\ngender_code : Male, Unknown, Female\n/\n" }, { "role": "user", "content": "List the id of students who attended statistics courses in the order of attendance date." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: courses, student_course_attendance.\nFrom these tables, I'll be using the following columns: student_course_attendance.student_id, courses.course_id, student_course_attendance.course_id, courses.course_name, statistics, student_course_attendance.date_of_attendance.\nThe SQL query I'll be generating is:\nSELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = \"statistics\" ORDER BY T2.date_of_attendance" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n/\n/\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE \"Artist\" (\n\t\"ArtistId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"ArtistId\")\n)\n/\nColumns in Artist and 3 examples in each column for high cardinality columns :\nArtistId : 87, 56, 65\nName : Smashing Pumpkins, Santana Feat. Eric Clapton, Godsmack\n/\n\n \nCREATE TABLE \"Department\" (\n\t\"DepartmentID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Head\" INTEGER NOT NULL, \n\tCONSTRAINT \"pk_Department\" PRIMARY KEY (\"DepartmentID\"), \n\tCONSTRAINT \"fk_Department_Physician_EmployeeID\" FOREIGN KEY(\"Head\") REFERENCES \"Physician\" (\"EmployeeID\")\n)\n/\nColumns in Department and all categories for low cardinality columns :\nDepartmentID : 1, 2, 3\nName : Psychiatry, Surgery, General Medicine\nHead : 7, 4, 9\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE film_market_estimation (\n\t\"Estimation_ID\" INTEGER, \n\t\"Low_Estimate\" REAL, \n\t\"High_Estimate\" REAL, \n\t\"Film_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Market_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Estimation_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in film_market_estimation and all categories for low cardinality columns :\nEstimation_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nLow_Estimate : 80000.0, 39.0, 16.0, 3000.0, 300.0, 53.0, 960.0, 913.0, 8000.0\nHigh_Estimate : 39.0, 16.0, 1000.0, 53.0, 960.0, 913.0, 8000.0, 80400.0\nFilm_ID : 1, 2, 4, 3\nType : Mass human sacrifice, Mass suicide murder, Mass suicide\nMarket_ID : 1, 2, 3\nYear : 1978, 1945, 1973, 1994, 1995, 2000, 1997, 1487, 1944\n/\n \nCREATE TABLE train (\n\tid INTEGER, \n\ttrain_number INTEGER, \n\tname TEXT, \n\torigin TEXT, \n\tdestination TEXT, \n\ttime TEXT, \n\tinterval TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\ntrain_number : 16526, 56700, 56701\ntime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nname : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\norigin : Quilon, Mumbai, Bangalore, Madurai, Nagercoil, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ndestination : Mumbai, Mangalore, Bangalore, Madurai, Quilon Junction, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ninterval : Daily\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n*/\n" }, { "role": "user", "content": "What are the ids of the students who attended courses in the statistics department in order of attendance date." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: courses, student_course_attendance.\nFrom these tables, I'll be using the following columns: student_course_attendance.student_id, courses.course_id, student_course_attendance.course_id, courses.course_name, statistics, student_course_attendance.date_of_attendance.\nThe SQL query I'll be generating is:\nSELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = \"statistics\" ORDER BY T2.date_of_attendance" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE branch (\n\t\"Branch_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Open_year\" TEXT, \n\t\"Address_road\" TEXT, \n\t\"City\" TEXT, \n\tmembership_amount TEXT, \n\tPRIMARY KEY (\"Branch_ID\")\n)\n/\nColumns in branch and all categories for low cardinality columns :\nBranch_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Popert, Zytogorski, Alexandre, Brooke Greville, Taverner, Stanley, Saint Amant, Cochrane\nOpen_year : 2009, 2013, 2015, 2001, 2012, 2014\nAddress_road : Abbott Street, Concord Road, Brampton Road, Cecilia Avenue, Oaks Crescent, Valleys Place, Glebe Street, Abbey Rise\nCity : Oxford, London\nmembership_amount : 91, 56, 11, 1418, 7, 6, 112, 31\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n/\n \nCREATE TABLE \"Lives_in\" (\n\tstuid INTEGER, \n\tdormid INTEGER, \n\troom_number INTEGER, \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid), \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Lives_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nroom_number : 153, 102, 301\n/\n/\nColumns in Lives_in and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"constructorStandings\" (\n\t\"constructorStandingsId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tpoints REAL, \n\tposition INTEGER, \n\t\"positionText\" TEXT, \n\twins INTEGER, \n\tPRIMARY KEY (\"constructorStandingsId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\")\n)\n/\nColumns in constructorStandings and 3 examples in each column for high cardinality columns :\nconstructorStandingsId : 87, 56, 65\nraceId : 21, 72, 71\nconstructorId : 1, 11, 2\npoints : 96.0, 8.0, 47.0\nposition : 1, 11, 2\npositionText : 1, 11, 2\n/\n/\nColumns in constructorStandings and all categories for low cardinality columns :\nwins : 1, 2, 5, 7, 8, 4, 6, 3, 0\n/\n \nCREATE TABLE \"Country\" (\n\tid INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Country and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\nname : Scotland, Italy, Spain\n/\n\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n/\n/\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n/\n/\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Claims_Processing\" (\n\t\"Claim_Processing_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Claim_Outcome_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Staff_ID\" INTEGER, \n\tPRIMARY KEY (\"Claim_Processing_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Processing and 3 examples in each column for high cardinality columns :\nClaim_Processing_ID : 243, 342, 818\n/\n/\nColumns in Claims_Processing and all categories for low cardinality columns :\nClaim_ID : 45, 28, 90, 24, 34, 62, 15, 27, 81\nClaim_Outcome_Code : Settled, In progress, Disputed\nClaim_Stage_ID : 1, 3\nStaff_ID : 771, 427, 510, 673, 986, 687, 822, 589, 718\n/\n \nCREATE TABLE \"Tracklists\" (\n\t\"AlbumId\" INTEGER, \n\t\"Position\" INTEGER, \n\t\"SongId\" INTEGER, \n\tPRIMARY KEY (\"AlbumId\", \"Position\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Albums\" (\"AId\")\n)\n/\nColumns in Tracklists and all categories for low cardinality columns :\nAlbumId : \nPosition : \nSongId : \n/\n \nCREATE TABLE church (\n\t\"Church_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Organized_by\" TEXT, \n\t\"Open_Date\" INTEGER, \n\t\"Continuation_of\" TEXT, \n\tPRIMARY KEY (\"Church_ID\")\n)\n/\nColumns in church and all categories for low cardinality columns :\nChurch_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Pure Church of Christ, True Church of Jesus Christ of Latter Day Saints, Alston Church, Church of Christ, Church of Jesus Christ, the Bride, the Lamb's Wife, Church of Christ (Parrishite), Independent Church\nOrganized_by : Hiram Page, George M. Hinkle, Isaac Russell, Wycam Clark, Ezra Booth, William Chubby, William Law, – Hoton, Warren Parrish\nOpen_Date : 1840, 1839, 1836, 1832, 1837, 1844, 1831, 1830, 1842\nContinuation_of : Church of Jesus Christ of Latter Day Saints, Church of Christ, Church of the Latter Day Saints\n/\n \nCREATE TABLE appellations (\n\t\"No\" INTEGER, \n\t\"Appelation\" TEXT, \n\t\"County\" TEXT, \n\t\"State\" TEXT, \n\t\"Area\" TEXT, \n\t\"isAVA\" TEXT, \n\tPRIMARY KEY (\"No\"), \n\tUNIQUE (\"Appelation\")\n)\n/\nColumns in appellations and 3 examples in each column for high cardinality columns :\nNo : 53, 56, 49\nAppelation : Anderson Valley, Fiddletown, Mendocino County\nCounty : Monterey, Solano, Santa Barbara\n/\n/\nColumns in appellations and all categories for low cardinality columns :\nState : California\nArea : Sierra Foothills, Central Valley, North Coast, Central Coast, N/A, California, Santa Cruz Mountains\nisAVA : Yes, No\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n" }, { "role": "user", "content": "Give me the dates when the max temperature was higher than 85." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: max_temperature_f.\nThe SQL query I'll be generating is:\nSELECT date FROM weather WHERE max_temperature_f > 85" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n/\n \nCREATE TABLE \"Albums\" (\n\t\"AId\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Label\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"AId\")\n)\n/\nColumns in Albums and all categories for low cardinality columns :\nAId : \nTitle : \nYear : \nLabel : \nType : \n/\n \nCREATE TABLE \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Participants_in_Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Participant_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\", \"Participant_ID\"), \n\tFOREIGN KEY(\"Participant_ID\") REFERENCES \"Participants\" (\"Participant_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/\nColumns in Participants_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n/\n/\nColumns in Participants_in_Events and all categories for low cardinality columns :\nParticipant_ID : 26, 86, 37, 90, 36, 96, 66, 63, 60, 64\n/\n \nCREATE TABLE mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\n/\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n \nCREATE TABLE news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE game (\n\tstadium_id INTEGER, \n\tid INTEGER, \n\t\"Season\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Home_team\" TEXT, \n\t\"Away_team\" TEXT, \n\t\"Score\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(stadium_id) REFERENCES stadium (id)\n)\n/\nColumns in game and 3 examples in each column for high cardinality columns :\nstadium_id : 1, 11, 2\nid : 17, 9, 16\nDate : 30 June 2013, 18 May 2007, 8 August 2009\nScore : 0–0 (7:6), –, 1–3\n/\n/\nColumns in game and all categories for low cardinality columns :\nSeason : 2009, 2013, 2008, 2012, 2011, 2010, 2007\nHome_team : Pakhtakor, Bunyodkor, Quruvchi\nAway_team : Pakhtakor, Bunyodkor, Quruvchi\nCompetition : League, Supercup, Cup\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n/\n \nCREATE TABLE \"Papers\" (\n\t\"paperID\" INTEGER, \n\ttitle TEXT, \n\tPRIMARY KEY (\"paperID\")\n)\n/\nColumns in Papers and all categories for low cardinality columns :\npaperID : 201, 204, 205, 200, 206, 203, 202\ntitle : Nameless, Painless, Binders Unbound, Proving the Unique Fixed-Point Principle Correct: An Adventure with Category Theory, An Equivalence-Preserving CPS Translation via Multi-Language Semantics, Making Standard ML a Practical Database Programming Language, Functional Pearl: Modular Rollback through Control Logging, Just do it: Simple Monadic Equational Reasoning\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n" }, { "role": "user", "content": "What are the dates with a maximum temperature higher than 85?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: max_temperature_f.\nThe SQL query I'll be generating is:\nSELECT date FROM weather WHERE max_temperature_f > 85" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Customer_Addresses\" (\n\tcustomer_id INTEGER NOT NULL, \n\tpremise_id INTEGER NOT NULL, \n\tdate_address_from DATETIME NOT NULL, \n\taddress_type_code VARCHAR(15) NOT NULL, \n\tdate_address_to DATETIME, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(premise_id) REFERENCES \"Premises\" (premise_id)\n)\n/\nColumns in Customer_Addresses and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ndate_address_from : 1975-04-23 20:41:01, 1939-01-15 17:55:39, 1990-12-19 22:02:27\ndate_address_to : 2018-03-08 08:03:51, 2018-03-15 18:34:41, 2018-03-16 11:55:11\n/\n/\nColumns in Customer_Addresses and all categories for low cardinality columns :\npremise_id : 1, 2, 5, 8, 4, 6, 12, 3, 14, 10\naddress_type_code : Billing, Shipping\n/\n \nCREATE TABLE \"Residents\" (\n\tresident_id INTEGER NOT NULL, \n\tproperty_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME NOT NULL, \n\tdate_moved_out DATETIME NOT NULL, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (resident_id, property_id, date_moved_in), \n\tFOREIGN KEY(property_id) REFERENCES \"Properties\" (property_id)\n)\n/\nColumns in Residents and 3 examples in each column for high cardinality columns :\nresident_id : 87, 38, 37\nproperty_id : 954, 120, 108\ndate_moved_out : 2018-01-28 13:19:54, 2017-11-14 06:28:48, 2018-02-22 06:24:15\nother_details : Anderson Batz, Jacques Glover II, Jess Wyman\n/\n/\nColumns in Residents and all categories for low cardinality columns :\ndate_moved_in : 2016-09-27 12:00:00, 2017-06-17 15:43:33, 2015-03-27 12:00:00\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n/\n \nCREATE TABLE \"View_Product_Availability\" (\n\tproduct_id INTEGER NOT NULL, \n\tbooking_id INTEGER NOT NULL, \n\tstatus_date DATETIME, \n\tavailable_yn VARCHAR(1), \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in View_Product_Availability and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 3\nbooking_id : 11, 5\nstatus_date : 2018-03-18 05:25:55, 2018-03-25 10:20:15, 2018-03-21 15:20:32, 2018-03-22 00:16:58\navailable_yn : 1, 0\n/\n \nCREATE TABLE \"SAVINGS\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/\nColumns in SAVINGS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 4, 6, 3\nbalance : 80000.0, 230000.0, 999999999.0, 60.0, 240.0, 200000.0\n/\n \nCREATE TABLE files (\n\tf_id NUMERIC(10) NOT NULL, \n\tartist_name TEXT(50), \n\tfile_size TEXT(20), \n\tduration TEXT(20), \n\tformats TEXT(20), \n\tPRIMARY KEY (f_id), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE\n)\n/\nColumns in files and all categories for low cardinality columns :\nf_id : 1.0000000000, 5.0000000000, 6.0000000000, 3.0000000000, 2.0000000000, 4.0000000000\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\nfile_size : 4.58 MB, 5.10 MB, 4.10 MB, 3.69 MB, 3.78 MB, 4.12 MB\nduration : 4:30, 5:23, 2:56, 4:34, 3:45, 4:12\nformats : mp3, mp4\n/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n/\n \nCREATE TABLE temperature (\n\t\"City_ID\" INTEGER, \n\t\"Jan\" REAL, \n\t\"Feb\" REAL, \n\t\"Mar\" REAL, \n\t\"Apr\" REAL, \n\t\"Jun\" REAL, \n\t\"Jul\" REAL, \n\t\"Aug\" REAL, \n\t\"Sep\" REAL, \n\t\"Oct\" REAL, \n\t\"Nov\" REAL, \n\t\"Dec\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"City_ID\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in temperature and all categories for low cardinality columns :\nCity_ID : 1, 11, 2, 7, 4, 6, 3, 10\nJan : 18.9, 25.6, 18.3, 26.1, 17.8, 26.7, 17.2\nFeb : 18.9, 18.3, 26.1, 27.2, 17.8, 26.6, 17.2\nMar : 19.4, 18.3, 26.1, 26.6, 27.8\nApr : 18.9, 26.1, 20.6, 28.3, 27.8, 20.0\nJun : 22.8, 30.0, 30.6, 22.2, 20.6, 28.3, 27.8, 20.0\nJul : 31.1, 23.3, 28.9, 30.6, 20.6, 21.7, 27.8\nAug : 31.1, 31.7, 23.9, 23.3, 29.4, 20.6, 21.7, 28.3\nSep : 31.1, 21.1, 31.7, 23.3, 29.4, 20.6, 28.3\nOct : 22.8, 30.6, 28.9, 20.6, 28.3, 20.0\nNov : 19.4, 27.2, 28.9, 21.7, 20.0\nDec : 18.3, 26.1, 26.7, 27.8, 20.0\n/\n \nCREATE TABLE furniture (\n\t\"Furniture_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Num_of_Component\" INTEGER, \n\t\"Market_Rate\" REAL, \n\tPRIMARY KEY (\"Furniture_ID\")\n)\n/\nColumns in furniture and all categories for low cardinality columns :\nFurniture_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dining set, Chabudai, Billiard table, Hatstand, Bookcase, Four-poster bed, Bench\nNum_of_Component : 5, 4, 6, 14, 3, 12\nMarket_Rate : 1.0, 3.5, 52.5, 0.5, 40.0, 2.0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What are the names of stations that have latitude lower than 37.5?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: name, lat.\nThe SQL query I'll be generating is:\nSELECT name FROM station WHERE lat < 37.5" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n/\n \nCREATE TABLE game (\n\tstadium_id INTEGER, \n\tid INTEGER, \n\t\"Season\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Home_team\" TEXT, \n\t\"Away_team\" TEXT, \n\t\"Score\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(stadium_id) REFERENCES stadium (id)\n)\n/\nColumns in game and 3 examples in each column for high cardinality columns :\nstadium_id : 1, 11, 2\nid : 17, 9, 16\nDate : 30 June 2013, 18 May 2007, 8 August 2009\nScore : 0–0 (7:6), –, 1–3\n/\n/\nColumns in game and all categories for low cardinality columns :\nSeason : 2009, 2013, 2008, 2012, 2011, 2010, 2007\nHome_team : Pakhtakor, Bunyodkor, Quruvchi\nAway_team : Pakhtakor, Bunyodkor, Quruvchi\nCompetition : League, Supercup, Cup\n/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"White\" REAL, \n\t\"Black\" REAL, \n\t\"Amerindian\" REAL, \n\t\"Asian\" REAL, \n\t\"Multiracial\" REAL, \n\t\"Hispanic\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"County_ID\") REFERENCES county_public_safety (\"County_ID\")\n)\n/\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 16, 13\nName : Aguadilla, Barranquitas, Bayamón\nWhite : 70.7, 78.3, 93.1\nBlack : 4.1, 22.8, 7.2\nMultiracial : 10.7, 12.1, 11.7\n/\n/\nColumns in city and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nAmerindian : 0.4, 0.6, 1.0, 0.3, 0.2, 0.9\nAsian : 0.1, 0.4, 0.3, 0.0, 0.2\nHispanic : 99.6, 98.5, 99.1, 99.5, 99.2, 99.4, 98.6, 98.9, 99.0, 99.3\n/\n \nCREATE TABLE route (\n\ttrain_id INTEGER, \n\tstation_id INTEGER, \n\tPRIMARY KEY (train_id, station_id), \n\tFOREIGN KEY(station_id) REFERENCES station (id), \n\tFOREIGN KEY(train_id) REFERENCES train (id)\n)\n/\nColumns in route and all categories for low cardinality columns :\ntrain_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nstation_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Residents_Services\" (\n\tresident_id INTEGER NOT NULL, \n\tservice_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME, \n\tproperty_id INTEGER, \n\tdate_requested DATETIME, \n\tdate_provided DATETIME, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (resident_id, service_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id), \n\tFOREIGN KEY(resident_id, property_id, date_moved_in) REFERENCES \"Residents\" (resident_id, property_id, date_moved_in)\n)\n/\nColumns in Residents_Services and 3 examples in each column for high cardinality columns :\nresident_id : 87, 67, 45\ndate_requested : 2017-07-14 19:03:47, 2016-07-25 01:32:23, 2016-06-18 20:09:24\ndate_provided : 2017-10-17 03:30:08, 2017-10-28 12:36:43, 2017-08-08 11:24:50\n/\n/\nColumns in Residents_Services and all categories for low cardinality columns :\nservice_id : 87, 65, 11, 49, 36, 10, 29, 41\ndate_moved_in : 2016-09-27 12:00:00, 2017-06-17 15:43:33, 2015-03-27 12:00:00\nproperty_id : 954, 120, 108, 629, 373, 748, 669, 445, 879, 107\nother_details : Satisfied, Unsatisfied\n/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n/\n/\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n/\n \nCREATE TABLE \"Lessons\" (\n\tlesson_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tlesson_status_code VARCHAR(15) NOT NULL, \n\tstaff_id INTEGER, \n\tvehicle_id INTEGER NOT NULL, \n\tlesson_date DATETIME, \n\tlesson_time VARCHAR(10), \n\tprice DOUBLE, \n\tPRIMARY KEY (lesson_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(vehicle_id) REFERENCES \"Vehicles\" (vehicle_id)\n)\n/\nColumns in Lessons and 3 examples in each column for high cardinality columns :\nlesson_id : 1, 13, 11\nlesson_date : 2018-03-03 15:10:16, 2018-03-07 16:12:36, 2018-03-08 16:05:05\nprice : 306.0, 492.0, 446.0\n/\n/\nColumns in Lessons and all categories for low cardinality columns :\ncustomer_id : 13, 11, 2, 5, 8, 6, 3, 10, 9\nlesson_status_code : Completed, Cancelled\nstaff_id : 1, 11, 5, 8, 4, 14, 3, 12, 15\nvehicle_id : 1, 2, 3\nlesson_time : 2, 5, 4, 6, 3, 9\n/\n \nCREATE TABLE manager (\n\t\"Manager_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Working_year_starts\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Manager_ID\")\n)\n/\nColumns in manager and all categories for low cardinality columns :\nManager_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ben Curtis, Sandy Lyle, Todd Hamilton, David Duval, Tiger Woods, Greg Norman, Nick Faldo\nCountry : United States, Australia, Scotland, England\nWorking_year_starts : 2004, 1993, 2001, 1985, 1999, 2006, 2003\nAge : 46, 45, 55, 48, 52, 47, 51\nLevel : 11, 5, 7, 8, 12\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n/\n" }, { "role": "user", "content": "What are the names of all stations with a latitude smaller than 37.5?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: name, lat.\nThe SQL query I'll be generating is:\nSELECT name FROM station WHERE lat < 37.5" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n/\n/\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE flight (\n\tflno NUMERIC(4, 0), \n\torigin TEXT(20), \n\tdestination TEXT(20), \n\tdistance NUMERIC(6, 0), \n\tdeparture_date DATE, \n\tarrival_date DATE, \n\tprice NUMERIC(7, 2), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (flno), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid)\n) \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_content VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tother_address_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_content : 92865 Margaretta Streets Suite 467, 78614 Maybell Alley Suite 057, 9443 Boyle Route Suite 857\ncity : South Meghanview, South Bellaland, Gleasonmouth\nzip_postcode : 721, 255, 416\nstate_province_county : RhodeIsland, Arizona, Mississippi\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\nother_address_details : None\n/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n/\n/\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n/\n \nCREATE TABLE machine (\n\t\"Machine_ID\" INTEGER, \n\t\"Making_Year\" INTEGER, \n\t\"Class\" TEXT, \n\t\"Team\" TEXT, \n\t\"Machine_series\" TEXT, \n\tvalue_points REAL, \n\tquality_rank INTEGER, \n\tPRIMARY KEY (\"Machine_ID\")\n)\n/\nColumns in machine and all categories for low cardinality columns :\nMachine_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMaking_Year : 1992, 1993, 1994, 1999, 1991, 1996, 1997, 1998, 1995\nClass : 125cc\nTeam : Honda, Team Givi- Honda LCR, Givi Racing- Honda, Marlboro Pileri - Honda, Hero Sports TS- Honda\nMachine_series : RS125\nvalue_points : 238.0, 105.0, 171.0, 129.0, 57.0, 62.0, 126.0, 194.0, 65.0\nquality_rank : 1, 13, 11, 2, 5, 7, 8, 4, 3\n/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n/\n \nCREATE TABLE \"Apartment_Facilities\" (\n\tapt_id INTEGER NOT NULL, \n\tfacility_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (apt_id, facility_code), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id)\n)\n/\nColumns in Apartment_Facilities and all categories for low cardinality columns :\napt_id : 1, 2, 5, 6, 3, 15, 9\nfacility_code : Gym, Swimming Pool, Boardband, Cable TV\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n/\n/\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n/\n" }, { "role": "user", "content": "For each city, return the highest latitude among its stations." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, lat.\nThe SQL query I'll be generating is:\nSELECT city , max(lat) FROM station GROUP BY city" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Dorm_amenity\" (\n\tamenid INTEGER, \n\tamenity_name VARCHAR(25)\n)\n/\nColumns in Dorm_amenity and 3 examples in each column for high cardinality columns :\namenid : 922, 955, 900\namenity_name : Study Room, Allows Pets, Roof\n/\n\n \nCREATE TABLE review (\n\ta_id INTEGER NOT NULL, \n\tu_id INTEGER NOT NULL, \n\ti_id INTEGER NOT NULL, \n\trating INTEGER DEFAULT NULL, \n\trank INTEGER DEFAULT NULL, \n\tPRIMARY KEY (a_id), \n\tFOREIGN KEY(i_id) REFERENCES item (i_id), \n\tFOREIGN KEY(u_id) REFERENCES useracct (u_id)\n)\n/\nColumns in review and all categories for low cardinality columns :\na_id : 1, 2, 5, 7, 4, 6, 3\nu_id : 1, 2\ni_id : 1, 5, 7, 4, 3\nrating : 7, 10, 5, 6\nrank : 1, 2, 5, 7, 4, 6, 3\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\taddress_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and all categories for low cardinality columns :\naddress_id : 1, 2, 5, 7, 8, 4, 6, 3, 9, 0\naddress_details : PT, IT, MX, US, DE, IE, ES\n/\n \nCREATE TABLE \"Apartment_Buildings\" (\n\tbuilding_id INTEGER NOT NULL, \n\tbuilding_short_name CHAR(15), \n\tbuilding_full_name VARCHAR(80), \n\tbuilding_description VARCHAR(255), \n\tbuilding_address VARCHAR(255), \n\tbuilding_manager VARCHAR(50), \n\tbuilding_phone VARCHAR(80), \n\tPRIMARY KEY (building_id), \n\tUNIQUE (building_id)\n)\n/\nColumns in Apartment_Buildings and 3 examples in each column for high cardinality columns :\nbuilding_id : 153, 734, 556\nbuilding_short_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_full_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_address : 012 Arnoldo Mountain\nGerholdland, ID 23342, 489 Josh Orchard Apt. 998\nSipesview, DE 69053, 601 Graham Roads\nPort Luz, VA 29660-6703\nbuilding_manager : Kyle, Emma, Kathlyn\nbuilding_phone : (948)040-1064x387, 1-724-982-9507x640, 544-148-5565x2847\n/\n/\nColumns in Apartment_Buildings and all categories for low cardinality columns :\nbuilding_description : Studio, Flat, Duplex\n/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n/\n \nCREATE TABLE \"Visitors\" (\n\t\"Tourist_ID\" INTEGER NOT NULL, \n\t\"Tourist_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Tourist_ID\"), \n\tUNIQUE (\"Tourist_ID\")\n)\n/\nColumns in Visitors and 3 examples in each column for high cardinality columns :\nTourist_ID : 241, 377, 779\nTourist_Details : Aleen, Lizzie, Vivian\n/\n\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n/\n \nCREATE TABLE \"Department_Store_Chain\" (\n\tdept_store_chain_id INTEGER, \n\tdept_store_chain_name VARCHAR(80), \n\tPRIMARY KEY (dept_store_chain_id)\n)\n/\nColumns in Department_Store_Chain and all categories for low cardinality columns :\ndept_store_chain_id : 1, 2, 4, 3\ndept_store_chain_name : West, East, North, South\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Student_Addresses\" (\n\tstudent_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_address_from DATETIME NOT NULL, \n\tdate_address_to DATETIME, \n\tmonthly_rental DECIMAL(19, 4), \n\tother_details VARCHAR(255), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Student_Addresses and 3 examples in each column for high cardinality columns :\nstudent_id : 1, 13, 11\naddress_id : 1, 16, 13\ndate_address_from : 2017-09-23 05:16:17, 2017-03-29 18:22:55, 2017-09-10 19:41:10\ndate_address_to : 2018-03-05 21:12:37, 2018-03-07 04:29:28, 2018-03-14 09:12:05\nmonthly_rental : 1032.8717, 1007.2597, 756.6745\n/\n/\nColumns in Student_Addresses and all categories for low cardinality columns :\nother_details : house, apartment\n/\n \nCREATE TABLE \"Accounts\" (\n\t\"Account_ID\" INTEGER NOT NULL, \n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Account_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Account_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Statements\" (\"Statement_ID\")\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\nAccount_ID : 321, 427, 240\nAccount_Details : 12223.93, 6352.31, 930.14\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\nStatement_ID : 192, 57\n/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n/\n/\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n/\n" }, { "role": "user", "content": "For each city, what is the highest latitude for its stations?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, lat.\nThe SQL query I'll be generating is:\nSELECT city , max(lat) FROM station GROUP BY city" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE \"Functional_Areas\" (\n\tfunctional_area_code VARCHAR(15), \n\tparent_functional_area_code VARCHAR(15), \n\tfunctional_area_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (functional_area_code)\n)\n/\nColumns in Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\nparent_functional_area_code : 8\nfunctional_area_description : Keep blank, Signature, Acknowledgement\n/\n \nCREATE TABLE \"Customer_Address_History\" (\n\tcustomer_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME NOT NULL, \n\tdate_to DATETIME, \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Address_History and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 10\ndate_from : 2009-02-16 23:04:20, 2008-06-22 21:50:44, 2011-01-02 21:42:29\ndate_to : 2018-03-20 01:13:38, 2018-03-11 20:16:56, 2018-03-24 06:20:36\n/\n/\nColumns in Customer_Address_History and all categories for low cardinality columns :\ncustomer_id : 13, 11, 2, 7, 6, 12, 3, 14, 9\n/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n/\n \nCREATE TABLE medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n/\n \nCREATE TABLE \"Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_Type_Code\" CHAR(15) NOT NULL, \n\t\"Start_Date\" DATETIME, \n\t\"End_Date\" DATETIME, \n\tPRIMARY KEY (\"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\")\n)\n/\nColumns in Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 703, 151, 768\nStart_Date : 2018-03-13 12:30:19, 2018-02-10 08:56:30, 2018-07-21 10:36:53\nEnd_Date : 2017-10-07 08:29:25, 2018-01-19 22:45:33, 2018-03-07 13:52:47\n/\n/\nColumns in Policies and all categories for low cardinality columns :\nCustomer_ID : 588, 858, 808, 334, 252, 994, 380, 430, 857, 435\nPolicy_Type_Code : Uniformed, Normal, Jurisdiction, Deputy\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE event (\n\t\"ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Stadium_ID\" INTEGER, \n\t\"Year\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Stadium_ID\") REFERENCES stadium (\"ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nID : 1, 2, 5, 4, 6, 3\nName : Pacific, European FINA, FINA, World Master, IPC, World Junior\nStadium_ID : 1, 2, 8, 4, 3, 10\nYear : 2016, 2013, 2012, 2017, 2011, 2014\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Birth_Date\" TEXT, \n\t\"Birth_Place\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 4, 6, 3\nName : Ty Conklin, Jake Gardiner, Al Montoya, Mark Fayne, Jack Campbell, Cam Fowler\nHeight : 215.0, 182.0, 195.0, 205.0, 192.0, 196.0\nWeight : 89.0, 100.0, 90.0, 102.0, 80.0, 92.0\nBirth_Date : December 5, 1991, May 5, 1987, July 4, 1990, February 13, 1985, March 30, 1976, January 1, 1992\nBirth_Place : Farmington Hills, Michigan, Anchorage, Alaska, Glenview, Illinois, Nashua, New Hampshire, Minnetonka, Minnesota, Port Huron, Michigan\n/\n \nCREATE TABLE happy_hour_member (\n\t\"HH_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Total_amount\" REAL, \n\tPRIMARY KEY (\"HH_ID\", \"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in happy_hour_member and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4\nMember_ID : 5, 9, 3\nTotal_amount : 4.9, 4.2, 20.9, 16.9, 16.92, 20.92\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "Give me the start station and end station for the trips with the three oldest id." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, end_station_name, id.\nThe SQL query I'll be generating is:\nSELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE project (\n\t\"Pname\" TEXT, \n\t\"Pnumber\" INTEGER, \n\t\"Plocation\" TEXT, \n\t\"Dnum\" INTEGER, \n\tPRIMARY KEY (\"Pnumber\")\n)\n/\nColumns in project and all categories for low cardinality columns :\nPname : Newbenefits, Reorganization, ProductX, Computerization, ProductZ, ProductY\nPnumber : 1, 20, 2, 30, 3, 10\nPlocation : Stafford, Sugarland, Bellaire, Houston\nDnum : 1, 4, 5\n/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Counties_Represented\" TEXT, \n\t\"District\" INTEGER, \n\t\"Delegate\" TEXT, \n\t\"Party\" INTEGER, \n\t\"First_Elected\" REAL, \n\t\"Committee\" TEXT, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"District\") REFERENCES county (\"County_Id\"), \n\tFOREIGN KEY(\"Party\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 7, 8, 4, 6, 3\nCounties_Represented : 09.1 9A, 13, 12.1 12A, 12.2 12B\nDistrict : 1, 2, 4, 3\nDelegate : Miller, Warren E. Warren E. Miller, Bobo, Elizabeth Elizabeth Bobo, Pendergrass, Shane E. Shane Pendergrass, Bates, Gail H. Gail H. Bates, DeBoy, Steven J. Sr. Steven J. DeBoy, Sr., Guzzone, Guy Guy Guzzone, Turner, Frank S. Frank S. Turner, Malone, James E. Jr. James E. Malone, Jr.\nParty : 1, 2, 7, 4, 3\nFirst_Elected : 2002.0, 2006.0, 1994.0, 2003.0\nCommittee : Environmental Matters, Economic Matters, Ways and Means, Environmental Matters (Vice-Chair), Health and Government Operations, Appropriations\n/\n \nCREATE TABLE railway (\n\t\"Railway_ID\" INTEGER, \n\t\"Railway\" TEXT, \n\t\"Builder\" TEXT, \n\t\"Built\" TEXT, \n\t\"Wheels\" TEXT, \n\t\"Location\" TEXT, \n\t\"ObjectNumber\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\")\n)\n/\nColumns in railway and all categories for low cardinality columns :\nRailway_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRailway : Longmoor, LTSR, GWRWk, GERSt, GWRSn, GERHt, MR, SECR, GWRS, GNRD\nBuilder : GNR Doncaster, Stephenson, Swindon Works, GWR Swindon, GER Stratford, MR Derby, GER Hartford, SECR Ashford, Avonside\nBuilt : 1902 Midland Railway 1000 was rebuilt in 1914., 1902, 1901, 1905, 1907, 1903, 1904, 1909, 1910\nWheels : 4-4-0, 4-6-0, 0-6-0T, 4-4-2, 4-4-2T, 2-8-0, 0-6-0, 0-6-0ST\nLocation : Shildon, Swindon, Basingstoke, York, Toddington, Barrow Hill, Bressingham, Bo'ness\nObjectNumber : 1975-7005, 1978-7028, 1978-7025, 1975-7003, 1978-7026, 2008-7159, 1975-7006, 1978-7027, 1975-7018, 1976-7001\n/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n/\n \nCREATE TABLE flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n/\n" }, { "role": "user", "content": "What is the station station and end station for the trips with the three smallest ids?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, end_station_name, id.\nThe SQL query I'll be generating is:\nSELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n/\n/\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n/\n \nCREATE TABLE \"Papers\" (\n\t\"paperID\" INTEGER, \n\ttitle TEXT, \n\tPRIMARY KEY (\"paperID\")\n)\n/\nColumns in Papers and all categories for low cardinality columns :\npaperID : 201, 204, 205, 200, 206, 203, 202\ntitle : Nameless, Painless, Binders Unbound, Proving the Unique Fixed-Point Principle Correct: An Adventure with Category Theory, An Equivalence-Preserving CPS Translation via Multi-Language Semantics, Making Standard ML a Practical Database Programming Language, Functional Pearl: Modular Rollback through Control Logging, Just do it: Simple Monadic Equational Reasoning\n/\n \nCREATE TABLE \"Timed_Status_of_Things\" (\n\tthing_id INTEGER NOT NULL, \n\t\"Date_and_Date\" DATETIME NOT NULL, \n\t\"Status_of_Thing_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (thing_id, \"Date_and_Date\", \"Status_of_Thing_Code\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id)\n)\n/\nColumns in Timed_Status_of_Things and 3 examples in each column for high cardinality columns :\nthing_id : 26, 80, 2\nDate_and_Date : 2017-06-19 02:59:21, 2017-08-05 02:10:02, 2016-10-08 08:02:57\n/\n/\nColumns in Timed_Status_of_Things and all categories for low cardinality columns :\nStatus_of_Thing_Code : Open, Close, In Progress\n/\n \nCREATE TABLE \"Document_Locations\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Date_in_Location_From\" DATETIME NOT NULL, \n\t\"Date_in_Locaton_To\" DATETIME, \n\tPRIMARY KEY (\"Document_ID\", \"Location_Code\", \"Date_in_Location_From\"), \n\tFOREIGN KEY(\"Location_Code\") REFERENCES \"Ref_Locations\" (\"Location_Code\"), \n\tFOREIGN KEY(\"Date_in_Location_From\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Date_in_Locaton_To\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"All_Documents\" (\"Document_ID\")\n)\n/\nColumns in Document_Locations and all categories for low cardinality columns :\nDocument_ID : 230, 11, 252, 170, 7, 119, 260, 111, 166, 81\nLocation_Code : b, e, c, n, x\nDate_in_Location_From : 2009-08-18 03:29:08, 1972-03-31 09:47:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1985-05-13 12:19:43, 2008-06-08 12:45:38\nDate_in_Locaton_To : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1995-01-01 03:52:11, 2008-06-08 12:45:38\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Accounts\" (\n\t\"Account_ID\" INTEGER NOT NULL, \n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Account_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Account_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Statements\" (\"Statement_ID\")\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\nAccount_ID : 321, 427, 240\nAccount_Details : 12223.93, 6352.31, 930.14\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\nStatement_ID : 192, 57\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Customers_Cards\" (\n\tcard_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tcard_type_code VARCHAR(15) NOT NULL, \n\tcard_number VARCHAR(80), \n\tdate_valid_from DATETIME, \n\tdate_valid_to DATETIME, \n\tother_card_details VARCHAR(255), \n\tPRIMARY KEY (card_id)\n)\n/\nColumns in Customers_Cards and 3 examples in each column for high cardinality columns :\ncard_id : 1, 13, 11\ncustomer_id : 3, 13, 10\ncard_number : 4560596484842, 4716674779726, 348237249146948\ndate_valid_from : 2013-05-23 07:55:36, 2012-05-22 02:05:41, 2013-11-17 02:58:22\ndate_valid_to : 2018-03-14 14:00:07, 2018-03-12 02:16:45, 2018-03-24 00:38:54\nother_card_details : 6011771512810699, 4916493714393, 5428692691195935\n/\n/\nColumns in Customers_Cards and all categories for low cardinality columns :\ncard_type_code : Credit, Debit\n/\n" }, { "role": "user", "content": "What is the average latitude and longitude of stations located in San Jose city?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: lat, city, San Jose.\nThe SQL query I'll be generating is:\nSELECT avg(lat) , avg(long) FROM station WHERE city = \"San Jose\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n/\n \nCREATE TABLE \"Electoral_Register\" (\n\telectoral_register_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (electoral_register_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Electoral_Register and all categories for low cardinality columns :\nelectoral_register_id : 2, 7, 8, 4, 6, 3\ncmi_cross_ref_id : 65, 75, 100, 83, 95\n/\n \nCREATE TABLE \"Parts\" (\n\tpart_id INTEGER, \n\tpart_name VARCHAR(255), \n\tchargeable_yn VARCHAR(1), \n\tchargeable_amount VARCHAR(20), \n\tother_part_details VARCHAR(255), \n\tPRIMARY KEY (part_id)\n)\n/\nColumns in Parts and all categories for low cardinality columns :\npart_id : 1, 2, 3\npart_name : top, middle, package\nchargeable_yn : 1, 0\nchargeable_amount : 4, 9\nother_part_details : None\n/\n \nCREATE TABLE \"Ref_Shipping_Agents\" (\n\tshipping_agent_code CHAR(15) NOT NULL, \n\tshipping_agent_name VARCHAR(255) NOT NULL, \n\tshipping_agent_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (shipping_agent_code)\n)\n/\nColumns in Ref_Shipping_Agents and all categories for low cardinality columns :\nshipping_agent_code : FE, UP, US, AL, SH\nshipping_agent_name : Airline, Fedex, UPS, USPS, Ship\nshipping_agent_description : t, q, k, w, g\n/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n/\n/\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n/\n \nCREATE TABLE trust (\n\tsource_u_id INTEGER NOT NULL, \n\ttarget_u_id INTEGER NOT NULL, \n\ttrust INTEGER NOT NULL, \n\tFOREIGN KEY(target_u_id) REFERENCES useracct (u_id), \n\tFOREIGN KEY(source_u_id) REFERENCES useracct (u_id)\n)\n/\nColumns in trust and all categories for low cardinality columns :\nsource_u_id : 1, 2, 7, 6, 3\ntarget_u_id : 2, 5, 4, 6, 3\ntrust : 1, 2, 7, 8, 4, 6, 3, 10\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_first_name VARCHAR(80), \n\tstaff_last_name VARCHAR(80), \n\tother_staff_details VARCHAR(255), \n\tPRIMARY KEY (staff_id)\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_first_name : Junius, Israel, Kenyatta\nstaff_last_name : Mante, Treutel, Weber\n/\n/\nColumns in Staff and all categories for low cardinality columns :\nother_staff_details : d, m, q, b, i, e, w, j, p, x\n/\n \nCREATE TABLE happy_hour_member (\n\t\"HH_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Total_amount\" REAL, \n\tPRIMARY KEY (\"HH_ID\", \"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in happy_hour_member and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4\nMember_ID : 5, 9, 3\nTotal_amount : 4.9, 4.2, 20.9, 16.9, 16.92, 20.92\n/\n \nCREATE TABLE \"Circulation_History\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tcopy_number INTEGER NOT NULL, \n\temployee_id INTEGER NOT NULL, \n\tPRIMARY KEY (document_id, draft_number, copy_number, employee_id), \n\tFOREIGN KEY(document_id, draft_number, copy_number) REFERENCES \"Draft_Copies\" (document_id, draft_number, copy_number), \n\tFOREIGN KEY(employee_id) REFERENCES \"Employees\" (employee_id)\n)\n/\nColumns in Circulation_History and all categories for low cardinality columns :\ndocument_id : 1, 10, 2, 20\ndraft_number : 1, 2, 17, 20\ncopy_number : 10, 15, 4, 5\nemployee_id : 1, 8, 2\n/\n \nCREATE TABLE airports (\n\tapid INTEGER, \n\tname TEXT NOT NULL, \n\tcity TEXT, \n\tcountry TEXT, \n\tx REAL, \n\ty REAL, \n\televation BIGINT, \n\tiata TEXT(3), \n\ticao TEXT(4), \n\tPRIMARY KEY (apid)\n)\n/\nColumns in airports and 3 examples in each column for high cardinality columns :\napid : 87, 56, 65\nname : Rouyn Noranda Airport, Edmonton International Airport, Val-d'Or Airport\ncity : Medicine Hat, Sarnia, Fort Saint John\nx : -117.4469985961914, -122.054000854, -135.067001343\ny : 45.5175018311, 50.29029846191406, 47.697400654599996\nelevation : 87, 586, 56\niata : NULL, YYE, YXJ\nicao : CYXD, CYBK, CYMO\n/\n/\nColumns in airports and all categories for low cardinality columns :\ncountry : Iceland, Papua New Guinea, Greenland, Canada\n/\n \nCREATE TABLE \"Procedures\" (\n\t\"Code\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Cost\" REAL NOT NULL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Procedures and all categories for low cardinality columns :\nCode : 1, 2, 5, 7, 4, 6, 3\nName : Obfuscated Dermogastrotomy, Obtuse Pyloric Recombobulation, Follicular Demiectomy, Reverse Rhinopodoplasty, Folded Demiophtalmectomy, Complete Walletectomy, Reversible Pancreomyoplasty\nCost : 5600.0, 1500.0, 10000.0, 25.0, 4500.0, 3750.0, 4899.0\n/\n \nCREATE TABLE \"Timed_Locations_of_Things\" (\n\tthing_id INTEGER NOT NULL, \n\t\"Date_and_Time\" DATETIME NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (thing_id, \"Date_and_Time\", \"Location_Code\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id)\n)\n/\nColumns in Timed_Locations_of_Things and 3 examples in each column for high cardinality columns :\nDate_and_Time : 2017-03-19 13:57:49, 2017-08-31 13:54:13, 2016-12-29 00:39:19\nLocation_Code : 2677 Runolfsson, 288 Lang Ferry, 94425 Nellie Kn\n/\n/\nColumns in Timed_Locations_of_Things and all categories for low cardinality columns :\nthing_id : 26, 45, 2, 68, 58, 92, 14, 85, 10\n/\n \nCREATE TABLE \"Restaurant_Type\" (\n\t\"ResTypeID\" INTEGER, \n\t\"ResTypeName\" VARCHAR(40), \n\t\"ResTypeDescription\" VARCHAR(100), \n\tPRIMARY KEY (\"ResTypeID\")\n)\n/\nColumns in Restaurant_Type and all categories for low cardinality columns :\nResTypeID : 1, 2\nResTypeName : Sandwich, Stir-fry\nResTypeDescription : Classic Chinese cooking., Simplest there is.\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Trained_In\" (\n\t\"Physician\" INTEGER NOT NULL, \n\t\"Treatment\" INTEGER NOT NULL, \n\t\"CertificationDate\" DATETIME NOT NULL, \n\t\"CertificationExpires\" DATETIME NOT NULL, \n\tPRIMARY KEY (\"Physician\", \"Treatment\"), \n\tCONSTRAINT \"fk_Trained_In_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Trained_In_Procedures_Code\" FOREIGN KEY(\"Treatment\") REFERENCES \"Procedures\" (\"Code\")\n)\n/\nColumns in Trained_In and all categories for low cardinality columns :\nPhysician : 7, 6, 3\nTreatment : 1, 2, 5, 7, 4, 6, 3\nCertificationDate : 2008-01-01 00:00:00, 2007-01-01 00:00:00\nCertificationExpires : 2007-12-31 00:00:00, 2008-12-31 00:00:00\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n" }, { "role": "user", "content": "What is the average latitude and longitude in San Jose?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: lat, city, San Jose.\nThe SQL query I'll be generating is:\nSELECT avg(lat) , avg(long) FROM station WHERE city = \"San Jose\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n/\n/\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n/\n \nCREATE TABLE \"PersonFriend\" (\n\tname VARCHAR(20), \n\tfriend VARCHAR(20), \n\tyear INTEGER, \n\tFOREIGN KEY(name) REFERENCES \"Person\" (name), \n\tFOREIGN KEY(friend) REFERENCES \"Person\" (name)\n)\n/\nColumns in PersonFriend and all categories for low cardinality columns :\nname : Alice, Zach, Bob\nfriend : Alice, Dan, Zach, Bob\nyear : 10, 5, 6, 12\n/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE \"Activity\" (\n\tactid INTEGER, \n\tactivity_name VARCHAR(25), \n\tPRIMARY KEY (actid)\n)\n/\nColumns in Activity and 3 examples in each column for high cardinality columns :\nactid : 771, 782, 770\nactivity_name : Proselytizing, Spelunking, Extreme Canasta\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE \"Customer_Contact_Channels\" (\n\tcustomer_id INTEGER NOT NULL, \n\tchannel_code VARCHAR(15) NOT NULL, \n\tactive_from_date DATETIME NOT NULL, \n\tactive_to_date DATETIME, \n\tcontact_number VARCHAR(50) NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Contact_Channels and 3 examples in each column for high cardinality columns :\nactive_from_date : 2017-05-25 16:08:45, 2017-06-21 06:41:19, 2018-03-01 10:17:18\nactive_to_date : 2018-03-16 14:00:15, 2018-02-24 00:57:39, 2018-03-20 14:01:12\ncontact_number : 940.035.6435x0225, 846.043.4809x0426, 1-968-863-4947x96956\n/\n/\nColumns in Customer_Contact_Channels and all categories for low cardinality columns :\ncustomer_id : 13, 2, 5, 15, 4, 6, 14, 3, 10, 9\nchannel_code : Mobile, Email, Fax, Handheld, Cell\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE film_market_estimation (\n\t\"Estimation_ID\" INTEGER, \n\t\"Low_Estimate\" REAL, \n\t\"High_Estimate\" REAL, \n\t\"Film_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Market_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Estimation_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in film_market_estimation and all categories for low cardinality columns :\nEstimation_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nLow_Estimate : 80000.0, 39.0, 16.0, 3000.0, 300.0, 53.0, 960.0, 913.0, 8000.0\nHigh_Estimate : 39.0, 16.0, 1000.0, 53.0, 960.0, 913.0, 8000.0, 80400.0\nFilm_ID : 1, 2, 4, 3\nType : Mass human sacrifice, Mass suicide murder, Mass suicide\nMarket_ID : 1, 2, 3\nYear : 1978, 1945, 1973, 1994, 1995, 2000, 1997, 1487, 1944\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What is the id of the trip that has the shortest duration?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration.\nThe SQL query I'll be generating is:\nSELECT id FROM trip ORDER BY duration LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Department\" (\n\t\"DNO\" INTEGER, \n\t\"Division\" VARCHAR(2), \n\t\"DName\" VARCHAR(25), \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\t\"DPhone\" INTEGER, \n\tPRIMARY KEY (\"DNO\")\n)\n/\nColumns in Department and 3 examples in each column for high cardinality columns :\nDNO : 170, 560, 540\nDName : Economics, Mechanical Engineering, English\nRoom : 206, 312, 440\nBuilding : Krieger, NEB, Latrobe\nDPhone : 7499, 7601, 7119\n/\n/\nColumns in Department and all categories for low cardinality columns :\nDivision : EN, AS\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE exhibition_record (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Exhibition_ID\", \"Date\"), \n\tFOREIGN KEY(\"Exhibition_ID\") REFERENCES exhibition (\"Exhibition_ID\")\n)\n/\nColumns in exhibition_record and 3 examples in each column for high cardinality columns :\nDate : February 25, February 19, December 2\nAttendance : 1313, 24808, 1233\n/\n/\nColumns in exhibition_record and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE wedding (\n\t\"Church_ID\" INTEGER, \n\t\"Male_ID\" INTEGER, \n\t\"Female_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Church_ID\", \"Male_ID\", \"Female_ID\"), \n\tFOREIGN KEY(\"Female_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Male_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Church_ID\") REFERENCES church (\"Church_ID\")\n)\n/\nColumns in wedding and all categories for low cardinality columns :\nChurch_ID : 1, 4, 5, 3\nMale_ID : 1, 7, 5, 3\nFemale_ID : 8, 2, 4, 6\nYear : 2015, 2016, 2014\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE festival_detail (\n\t\"Festival_ID\" INTEGER, \n\t\"Festival_Name\" TEXT, \n\t\"Chair_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Festival_ID\")\n)\n/\nColumns in festival_detail and all categories for low cardinality columns :\nFestival_ID : 1, 2, 5, 4, 3\nFestival_Name : Gobel Awards, LA Awards, Flower Awards, Panasonic Awards, Cherry Awards\nChair_Name : Doug Ford, Charles Coody, Lucy Lu, Arnold Palmer, Raymond Floyd\nLocation : United States\nYear : 2007, 2008, 2010, 2006\nNum_of_Audience : 160, 152, 161, 155\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tparent_product_id INTEGER, \n\tproduct_category_code VARCHAR(20) NOT NULL, \n\tdate_product_first_available DATETIME, \n\tdate_product_discontinued DATETIME, \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tproduct_price DECIMAL(19, 4), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\nparent_product_id : 8, 4, 9, 3\nproduct_category_code : Food, Book, Hardware\ndate_product_first_available : 1988-09-29 17:54:50, 1998-06-20 15:04:11, 1994-12-18 15:13:19, 1974-06-25 12:26:47\ndate_product_discontinued : 1987-12-20 13:46:16, 1997-07-02 18:26:16, 1980-06-26 10:40:19, 1991-08-20 05:22:31\nproduct_name : Chocolate, The Great Gatsby, Mouse, Keyboard\nproduct_description : Designed for games, Handmade chocolate, American novel, Blue tooth mouse\nproduct_price : 23.3500, 2.8800, 109.9900, 35.0000\n/\n \nCREATE TABLE repair_assignment (\n\ttechnician_id INTEGER, \n\t\"repair_ID\" INTEGER, \n\t\"Machine_ID\" INTEGER, \n\tPRIMARY KEY (technician_id, \"repair_ID\", \"Machine_ID\"), \n\tFOREIGN KEY(\"Machine_ID\") REFERENCES machine (\"Machine_ID\"), \n\tFOREIGN KEY(\"repair_ID\") REFERENCES repair (\"repair_ID\"), \n\tFOREIGN KEY(technician_id) REFERENCES technician (technician_id)\n)\n/\nColumns in repair_assignment and all categories for low cardinality columns :\ntechnician_id : 1, 2, 5, 7, 3\nrepair_ID : 1, 2, 5, 8, 4, 3\nMachine_ID : 1, 2, 7, 4, 6, 3\n/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n \nCREATE TABLE manufacturer (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Open_Year\" REAL, \n\t\"Name\" TEXT, \n\t\"Num_of_Factories\" INTEGER, \n\t\"Num_of_Shops\" INTEGER, \n\tPRIMARY KEY (\"Manufacturer_ID\")\n)\n/\nColumns in manufacturer and all categories for low cardinality columns :\nManufacturer_ID : 1, 2, 5, 7, 4, 6, 3\nOpen_Year : 2001.0, 2008.0, 2000.0, 1980.0, 1992.0, 1991.0, 1990.0\nName : Tomorrow, Chevrolet, Chevrolet House, Jiaju, Ford Make, IKEA, Dodge\nNum_of_Factories : 1, 38, 36, 21, 12, 3\nNum_of_Shops : 2, 7, 8, 24, 4, 19, 35\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE party (\n\t\"Party_ID\" INTEGER, \n\t\"Minister\" TEXT, \n\t\"Took_office\" TEXT, \n\t\"Left_office\" TEXT, \n\t\"Region_ID\" INTEGER, \n\t\"Party_name\" TEXT, \n\tPRIMARY KEY (\"Party_ID\"), \n\tFOREIGN KEY(\"Region_ID\") REFERENCES region (\"Region_ID\")\n)\n/\nColumns in party and all categories for low cardinality columns :\nParty_ID : 1, 2, 5, 4, 3\nMinister : Kojo Botsio (MP), Ebenezer Ako-Adjei (MP), Dr. Kwame Nkrumah (MP), Imoru Egala (MP)\nTook_office : 1958, 1961, 1959, 1960, 1957\nLeft_office : 1962, 1958, 1961, 1959, 1960\nRegion_ID : 1, 2, 5, 4, 3\nParty_name : Convention Peoples Party, Sinefine Party, Convention Union Party, 3, Progress Party\n/\n \nCREATE TABLE channel (\n\t\"Channel_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Owner\" TEXT, \n\t\"Share_in_percent\" REAL, \n\t\"Rating_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/\nColumns in channel and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Shandong Satellite TV, CCTV-8, Hunan Satellite TV, CCTV-3, CCTV-14, CCTV-6, CCTV-13, CCTV-1, Anhui Satellite TV, CCTV-4\nOwner : HBS, Shandong Television, CCTV, Anhui Television\nShare_in_percent : 4.9, 2.33, 1.74, 2.91, 4.81, 2.6, 2.86, 3.76, 1.78, 2.73\nRating_in_percent : 0.53, 0.41, 0.32, 0.19, 0.54, 0.3, 0.31, 0.2, 0.29, 0.26\n/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n/\n/\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n/\n" }, { "role": "user", "content": "What is the id of the shortest trip?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration.\nThe SQL query I'll be generating is:\nSELECT id FROM trip ORDER BY duration LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Students_in_Detention\" (\n\tstudent_id INTEGER NOT NULL, \n\tdetention_id INTEGER NOT NULL, \n\tincident_id INTEGER NOT NULL, \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(detention_id) REFERENCES \"Detention\" (detention_id), \n\tFOREIGN KEY(incident_id) REFERENCES \"Behavior_Incident\" (incident_id)\n)\n/\nColumns in Students_in_Detention and all categories for low cardinality columns :\nstudent_id : 3, 13, 11, 7, 8, 14, 12, 10, 9\ndetention_id : 3, 13, 2, 7, 6, 12, 14, 15, 9\nincident_id : 1, 13, 11, 8, 12, 3, 14, 15\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n/\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER NOT NULL, \n\tparent_organization_id INTEGER, \n\torganization_details VARCHAR(255), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 7, 8, 10\nparent_organization_id : 7, 8\norganization_details : Denesik and Sons Party, Reinger, Hudson and Nolan Group, Robel-Schulist Group\n/\n \nCREATE TABLE \"Documents\" (\n\tdocument_id INTEGER NOT NULL, \n\tdocument_status_code CHAR(15) NOT NULL, \n\tdocument_type_code CHAR(15) NOT NULL, \n\tshipping_agent_code CHAR(15), \n\treceipt_date DATETIME, \n\treceipt_number VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (document_id), \n\tFOREIGN KEY(document_type_code) REFERENCES \"Ref_Document_Types\" (document_type_code), \n\tFOREIGN KEY(document_status_code) REFERENCES \"Ref_Document_Status\" (document_status_code), \n\tFOREIGN KEY(shipping_agent_code) REFERENCES \"Ref_Shipping_Agents\" (shipping_agent_code)\n)\n/\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_id : 1, 13, 20\nreceipt_date : 2014-12-25 17:22:44, 2008-04-21 20:42:25, 2015-04-03 09:36:19\nreceipt_number : 79, 114, 69\nother_details : m, q, b\n/\n/\nColumns in Documents and all categories for low cardinality columns :\ndocument_status_code : done, overdue, working\ndocument_type_code : Hard Drive, CD, Paper\nshipping_agent_code : FE, UP, US, AL, SH\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE \"Has_amenity\" (\n\tdormid INTEGER, \n\tamenid INTEGER, \n\tFOREIGN KEY(amenid) REFERENCES \"Dorm_amenity\" (amenid), \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid)\n)\n/\nColumns in Has_amenity and 3 examples in each column for high cardinality columns :\namenid : 902, 955, 930\n/\n/\nColumns in Has_amenity and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n/\n \nCREATE TABLE grapes (\n\t\"ID\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Color\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tUNIQUE (\"Grape\")\n)\n/\nColumns in grapes and 3 examples in each column for high cardinality columns :\nID : 17, 9, 16\nGrape : Marsanne, Tempranillo, Malbec\n/\n/\nColumns in grapes and all categories for low cardinality columns :\nColor : Red, White\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE device (\n\t\"Device_ID\" INTEGER, \n\t\"Device\" TEXT, \n\t\"Carrier\" TEXT, \n\t\"Package_Version\" TEXT, \n\t\"Applications\" TEXT, \n\t\"Software_Platform\" TEXT, \n\tPRIMARY KEY (\"Device_ID\")\n)\n/\nColumns in device and all categories for low cardinality columns :\nDevice_ID : 1, 2, 5, 4, 6, 3\nDevice : Huawei, Galaxy, Apple, Xiaomi, BlackBerry Storm 9530, Samsung\nCarrier : MTS Mobility, Bell Mobility, Telus Mobility, Vodafone AU, Verizon Wireless, Iusacell\nPackage_Version : 4.7.0.208, 5.0.0.742, 5.0.0.808, 5.0.0.328, 5.0.0.419\nApplications : 4.7.0.151, 5.0.0.451, 5.0.0.328, 5.0.0.419\nSoftware_Platform : iOS, Android\n/\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\ttown_city VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 90928 Garret Mall, 25518 Ortiz Centers, 3986 Bergstrom Stravenue\ntown_city : Robertsberg, East Clair, Dangelohaven\nzip_postcode : 250, 193, 021\nstate_province_county : Pennsylvania, Michigan, NewHampshire\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n" }, { "role": "user", "content": "What is the total and maximum duration of trips with bike id 636?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: duration, bike_id.\nThe SQL query I'll be generating is:\nSELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n/\n/\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n/\n \nCREATE TABLE body_builder (\n\t\"Body_Builder_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Snatch\" REAL, \n\t\"Clean_Jerk\" REAL, \n\t\"Total\" REAL, \n\tPRIMARY KEY (\"Body_Builder_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in body_builder and all categories for low cardinality columns :\nBody_Builder_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 2, 5, 6, 3\nSnatch : 142.5, 137.5, 130.0, 140.0\nClean_Jerk : 162.5, 177.5, 175.0\nTotal : 315.0, 317.5, 312.5, 292.5\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE teachers (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/\nColumns in teachers and 3 examples in each column for high cardinality columns :\nLastName : MOYER, NIBLER, ONDERSMA\nFirstName : CHARMAINE, JEROME, KIRK\nClassroom : 109, 108, 106\n/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE train (\n\tid INTEGER, \n\ttrain_number INTEGER, \n\tname TEXT, \n\torigin TEXT, \n\tdestination TEXT, \n\ttime TEXT, \n\tinterval TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\ntrain_number : 16526, 56700, 56701\ntime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nname : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\norigin : Quilon, Mumbai, Bangalore, Madurai, Nagercoil, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ndestination : Mumbai, Mangalore, Bangalore, Madurai, Quilon Junction, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ninterval : Daily\n/\n \nCREATE TABLE \"Ship\" (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Built_Year\" REAL, \n\t\"Class\" TEXT, \n\t\"Flag\" TEXT, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/\nColumns in Ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : HMS Trojan, HMS Destiny, HMS Phalarope, HMS Undine, HMS Manxman, HM Cutter Avenger, HM Sloop Sparrow, HM Schooner Hotspur, HMS Gorgon\nType : Panamax\nBuilt_Year : 1997.0, 1998.0\nClass : GL, KR\nFlag : Panama, Malta\n/\n \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tservice_type_code CHAR(15) NOT NULL, \n\tservice_details VARCHAR(255), \n\tPRIMARY KEY (service_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 87, 41, 65\n/\n/\nColumns in Services and all categories for low cardinality columns :\norganization_id : 7, 10, 8\nservice_type_code : Cleanning, Moving Out, Check, Pay bills\nservice_details : Satisfied, Unsatisfied\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (\"Service_ID\")\n)\n/\nColumns in Services and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nService_Type_Code : Marriage, Birth Proof, Death Proof, Property Change\n/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"City\" TEXT, \n\t\"Hanzi\" TEXT, \n\t\"Hanyu_Pinyin\" TEXT, \n\t\"Regional_Population\" INTEGER, \n\t\"GDP\" REAL, \n\tPRIMARY KEY (\"City_ID\")\n)\n/\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 13, 11\nCity : Shanghai, Changzhou ( Jiangsu ), Jinhua ( Zhejiang )\nHanzi : 台州, 金华/ 金華, 上海\nHanyu_Pinyin : Shàoxīng, Tāizhōu, Hángzhōu\nRegional_Population : 8700400, 7605689, 4912200\nGDP : 1919.57, 408.02, 266.81\n/\n\n" }, { "role": "user", "content": "What is the total and maximum duration for all trips with the bike id 636?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: duration, bike_id.\nThe SQL query I'll be generating is:\nSELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE hosting_city (\n\t\"Year\" INTEGER, \n\t\"Match_ID\" INTEGER, \n\t\"Host_City\" TEXT, \n\tPRIMARY KEY (\"Year\"), \n\tFOREIGN KEY(\"Match_ID\") REFERENCES \"match\" (\"Match_ID\"), \n\tFOREIGN KEY(\"Host_City\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in hosting_city and all categories for low cardinality columns :\nYear : 2009, 2013, 2012, 2008, 2011, 2010\nMatch_ID : 1, 2, 5, 4, 6, 3\nHost_City : 1, 11, 2, 6, 12\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE aircraft (\n\t\"Aircraft_ID\" INTEGER, \n\t\"Order_Year\" INTEGER, \n\t\"Manufacturer\" TEXT, \n\t\"Model\" TEXT, \n\t\"Fleet_Series\" TEXT, \n\t\"Powertrain\" TEXT, \n\t\"Fuel_Propulsion\" TEXT, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 7, 4, 6, 3\nOrder_Year : 1992, 2000, 1996, 2002, 1998, 2011, 2010\nManufacturer : NFI, Gillig\nModel : C40LFR, GE40LFR, Phantom (High Floor), Advantage (Low Floor)\nFleet_Series : 310-329 (20), 465-467 (3), 468-473 (6), 444-464 (21), 474-481 (8), 300-309 (10), 482-492 (11)\nPowertrain : Cummins Westport ISL-G Allison WB-400R, Cummins ISC Allison WB-400R, DD S50 Allison WB-400R, Cummins ISL Allison WB-400R, Ford Triton V10 ISE-Thundervolt TB40-HG, DD S50EGR Allison WB-400R\nFuel_Propulsion : Hybrid, Diesel, CNG\n/\n \nCREATE TABLE csu_fees (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"CampusFee\" INTEGER, \n\tPRIMARY KEY (\"Campus\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in csu_fees and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nCampusFee : 1916, 2009, 2204\n/\n/\nColumns in csu_fees and all categories for low cardinality columns :\nYear : 2003, 1996\n/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n \nCREATE TABLE club_rank (\n\t\"Rank\" REAL, \n\t\"Club_ID\" INTEGER, \n\t\"Gold\" REAL, \n\t\"Silver\" REAL, \n\t\"Bronze\" REAL, \n\t\"Total\" REAL, \n\tPRIMARY KEY (\"Rank\", \"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in club_rank and all categories for low cardinality columns :\nRank : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nClub_ID : 1, 2, 5, 4, 6, 3\nGold : 8.0, 3.0, 11.0, 7.0, 2.0, 4.0\nSilver : 3.0, 11.0, 1.0, 7.0, 2.0, 4.0\nBronze : 6.0, 9.0, 0.0, 2.0\nTotal : 3.0, 12.0, 13.0, 6.0, 21.0, 31.0\n/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n/\n/\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n/\n/\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n" }, { "role": "user", "content": "For each zip code, return the average mean temperature of August there." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_temperature_f, 8/%.\nThe SQL query I'll be generating is:\nSELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE \"8/%\" GROUP BY zip_code" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Card_Number\" TEXT, \n\t\"Name\" TEXT, \n\t\"Hometown\" TEXT, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nCard_Number : LT98, RE95, LCB7, FS10, MLB4, SLB51, RCB32, OLB56, LE99, RT91\nName : Trevard Lindley, Jeremy Jarmon, Corey Peters, David Jones, Myron Pryor, Matt Lentz, Johnny Williams, Ventrell Jenkins, Braxton Kelley, Micah Johnson\nHometown : Jacksonville, Florida, Collierville, Tennessee, Columbia, South Carolina, Red Jacket, West Virginia, Fort Campbell, Kentucky, LaGrange, Georgia, Louisville, Kentucky, Simpsonville, South Carolina, Hiram, Georgia\nLevel : 2, 4, 6\n/\n \nCREATE TABLE \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\n/\n \nCREATE TABLE machine (\n\t\"Machine_ID\" INTEGER, \n\t\"Making_Year\" INTEGER, \n\t\"Class\" TEXT, \n\t\"Team\" TEXT, \n\t\"Machine_series\" TEXT, \n\tvalue_points REAL, \n\tquality_rank INTEGER, \n\tPRIMARY KEY (\"Machine_ID\")\n)\n/\nColumns in machine and all categories for low cardinality columns :\nMachine_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMaking_Year : 1992, 1993, 1994, 1999, 1991, 1996, 1997, 1998, 1995\nClass : 125cc\nTeam : Honda, Team Givi- Honda LCR, Givi Racing- Honda, Marlboro Pileri - Honda, Hero Sports TS- Honda\nMachine_series : RS125\nvalue_points : 238.0, 105.0, 171.0, 129.0, 57.0, 62.0, 126.0, 194.0, 65.0\nquality_rank : 1, 13, 11, 2, 5, 7, 8, 4, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n/\n/\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n/\n \nCREATE TABLE \"View_Product_Availability\" (\n\tproduct_id INTEGER NOT NULL, \n\tbooking_id INTEGER NOT NULL, \n\tstatus_date DATETIME, \n\tavailable_yn VARCHAR(1), \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in View_Product_Availability and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 3\nbooking_id : 11, 5\nstatus_date : 2018-03-18 05:25:55, 2018-03-25 10:20:15, 2018-03-21 15:20:32, 2018-03-22 00:16:58\navailable_yn : 1, 0\n/\n \nCREATE TABLE \"Ref_Transaction_Types\" (\n\ttransaction_type_code VARCHAR(10), \n\ttransaction_type_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (transaction_type_code)\n)\n/\nColumns in Ref_Transaction_Types and all categories for low cardinality columns :\ntransaction_type_code : PUR, SALE\ntransaction_type_description : Sale, Purchase\n/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n/\n \nCREATE TABLE railway_manage (\n\t\"Railway_ID\" INTEGER, \n\t\"Manager_ID\" INTEGER, \n\t\"From_Year\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\", \"Manager_ID\"), \n\tFOREIGN KEY(\"Manager_ID\") REFERENCES manager (\"Manager_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in railway_manage and all categories for low cardinality columns :\nRailway_ID : 7, 8, 2, 9\nManager_ID : 1, 2, 4, 3\nFrom_Year : 2012, 2010, 2011, 2013\n/\n \nCREATE TABLE \"Plays_Games\" (\n\t\"StuID\" INTEGER, \n\t\"GameID\" INTEGER, \n\t\"Hours_Played\" INTEGER, \n\tFOREIGN KEY(\"GameID\") REFERENCES \"Video_Games\" (\"GameID\"), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Plays_Games and all categories for low cardinality columns :\nStuID : 1007, 1008, 1032, 1010, 1001\nGameID : 1, 2, 5, 4, 6, 3\nHours_Played : 1, 100, 10, 1000, 50, 47, 15, 1337, 35\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Product_Characteristics\" (\n\tproduct_id INTEGER NOT NULL, \n\tcharacteristic_id INTEGER NOT NULL, \n\tproduct_characteristic_value VARCHAR(50), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(characteristic_id) REFERENCES \"Characteristics\" (characteristic_id)\n)\n/\nColumns in Product_Characteristics and all categories for low cardinality columns :\nproduct_id : 1, 13, 11, 5, 7, 8, 6, 12, 14\ncharacteristic_id : 13, 10, 11, 2, 4, 6, 12, 3, 15\nproduct_characteristic_value : high, low, medium\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n" }, { "role": "user", "content": "For each zip code, what is the average mean temperature for all dates that start with '8'?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_temperature_f, 8/%.\nThe SQL query I'll be generating is:\nSELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE \"8/%\" GROUP BY zip_code" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE debate (\n\t\"Debate_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Debate_ID\")\n)\n/\nColumns in debate and all categories for low cardinality columns :\nDebate_ID : 1, 2, 5, 4, 6, 3\nDate : October 21, 2011, December 17, 2014, August 3, 2015, January 21, 2017, October 27, 2015, January 12, 2017\nVenue : Abu Dhabi , UAE, Doha , Qatar, Dubai , UAE, Manama , Bahrain\nNum_of_Audience : 342, 159, 90, 209, 313, 134\n/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n/\n/\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n/\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n/\n \nCREATE TABLE stadium (\n\tid INTEGER, \n\tname TEXT, \n\t\"Home_Games\" INTEGER, \n\t\"Average_Attendance\" REAL, \n\t\"Total_Attendance\" REAL, \n\t\"Capacity_Percentage\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in stadium and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Gillette Stadium, Lincoln Financial Field, New Meadowlands Stadium\nAverage_Attendance : 70038.0, 87047.0, 71227.0\nTotal_Attendance : 553144.0, 566362.0, 550048.0\n/\n/\nColumns in stadium and all categories for low cardinality columns :\nHome_Games : 8\nCapacity_Percentage : 96.0, 108.8, 100.3, 100.0, 95.8, 90.7, 102.3, 98.4, 97.1, 95.3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n/\n/\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n/\n/\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n/\n \nCREATE TABLE host (\n\t\"Host_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\tPRIMARY KEY (\"Host_ID\")\n)\n/\nColumns in host and all categories for low cardinality columns :\nHost_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Lloyd Daniels, Kornel David, Antonio Davis, Carlos Delfino, DeMar DeRozan, Ed Davis, Austin Daye, Derrick Dial, Justin Dentmon, Hubert Davis\nNationality : United States, Argentina, Hungary\nAge : 26, 45, 37, 40, 30, 60, 47, 43, 31\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n/\n \nCREATE TABLE \"Catalog_Contents\" (\n\tcatalog_entry_id INTEGER, \n\tcatalog_level_number INTEGER NOT NULL, \n\tparent_entry_id INTEGER, \n\tprevious_entry_id INTEGER, \n\tnext_entry_id INTEGER, \n\tcatalog_entry_name VARCHAR(80), \n\tproduct_stock_number VARCHAR(50), \n\tprice_in_dollars DOUBLE, \n\tprice_in_euros DOUBLE, \n\tprice_in_pounds DOUBLE, \n\tcapacity VARCHAR(20), \n\tlength VARCHAR(20), \n\theight VARCHAR(20), \n\twidth VARCHAR(20), \n\tPRIMARY KEY (catalog_entry_id), \n\tFOREIGN KEY(catalog_level_number) REFERENCES \"Catalog_Structure\" (catalog_level_number)\n)\n/\nColumns in Catalog_Contents and 3 examples in each column for high cardinality columns :\ncatalog_entry_id : 1, 13, 11\ncatalog_entry_name : Cream Soda, Diet Pepsi, Ramune\nproduct_stock_number : 15 mr, 42 cp, 26 op\nprice_in_dollars : 475.79, 687.59, 616.22\nprice_in_euros : 385.85, 159.84, 537.66\nprice_in_pounds : 440.52, 405.75, 331.43\n/\n/\nColumns in Catalog_Contents and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\nparent_entry_id : 5, 7, 4, 6, 3\nprevious_entry_id : 5, 7, 8, 4, 6, 3, 9\nnext_entry_id : 1, 7, 8, 6, 3, 9\ncapacity : 1, 5, 7, 8, 4, 6, 9\nlength : 5, 7, 8, 4, 6, 3, 9\nheight : 1, 2, 5, 7, 8, 4, 6, 3, 9\nwidth : 1, 5, 7, 8, 6, 3, 9\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "From the trip record, find the number of unique bikes." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: bike_id.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT bike_id) FROM trip" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n/\n/\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n/\n \nCREATE TABLE pilot_record (\n\t\"Record_ID\" INTEGER, \n\t\"Pilot_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\t\"Date\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\", \"Aircraft_ID\", \"Date\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Pilot_ID\") REFERENCES pilot (\"Pilot_ID\")\n)\n/\nColumns in pilot_record and all categories for low cardinality columns :\nRecord_ID : 1, 2, 5, 4, 6, 3\nPilot_ID : 1, 2, 4, 3\nAircraft_ID : 1, 2, 5, 4, 6\nDate : 2006/01/04, 2005/01/04, 2008/01/04, 2004/01/04, 2007/01/04, 2003/01/04\n/\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE tweets (\n\tid BIGINT NOT NULL, \n\tuid INTEGER NOT NULL, \n\ttext CHAR(140) NOT NULL, \n\tcreatedate DATETIME DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(uid) REFERENCES user_profiles (uid)\n)\n/\nColumns in tweets and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 9\nuid : 1, 5, 4, 6, 3\ntext : Today I have went shopping at Laffayette., Let’s celebrate women, fight for equality and support each other, not just today, but everyday!, Oh, I only have a few fans., I love my new boyfriend., I feel tired and don't want to write SQLs., My company is hiring interns., Hello I'm Tony Stark., I had a pretty rough time during the last couple of weeks\ncreatedate : 2018-03-09 20:00:14, 2018-03-12 02:30:30, 2018-03-09 20:01:02\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n \nCREATE TABLE \"Assets\" (\n\t\"Asset_ID\" INTEGER NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Asset_ID\")\n)\n/\nColumns in Assets and all categories for low cardinality columns :\nAsset_ID : 1, 2, 3\nOther_Details : Meeting Rooms, Dinning Tables, Transportation Cars\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE aircraft (\n\t\"Aircraft_ID\" INTEGER, \n\t\"Order_Year\" INTEGER, \n\t\"Manufacturer\" TEXT, \n\t\"Model\" TEXT, \n\t\"Fleet_Series\" TEXT, \n\t\"Powertrain\" TEXT, \n\t\"Fuel_Propulsion\" TEXT, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 7, 4, 6, 3\nOrder_Year : 1992, 2000, 1996, 2002, 1998, 2011, 2010\nManufacturer : NFI, Gillig\nModel : C40LFR, GE40LFR, Phantom (High Floor), Advantage (Low Floor)\nFleet_Series : 310-329 (20), 465-467 (3), 468-473 (6), 444-464 (21), 474-481 (8), 300-309 (10), 482-492 (11)\nPowertrain : Cummins Westport ISL-G Allison WB-400R, Cummins ISC Allison WB-400R, DD S50 Allison WB-400R, Cummins ISL Allison WB-400R, Ford Triton V10 ISE-Thundervolt TB40-HG, DD S50EGR Allison WB-400R\nFuel_Propulsion : Hybrid, Diesel, CNG\n/\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE files (\n\tf_id NUMERIC(10) NOT NULL, \n\tartist_name TEXT(50), \n\tfile_size TEXT(20), \n\tduration TEXT(20), \n\tformats TEXT(20), \n\tPRIMARY KEY (f_id), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE\n)\n/\nColumns in files and all categories for low cardinality columns :\nf_id : 1.0000000000, 5.0000000000, 6.0000000000, 3.0000000000, 2.0000000000, 4.0000000000\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\nfile_size : 4.58 MB, 5.10 MB, 4.10 MB, 3.69 MB, 3.78 MB, 4.12 MB\nduration : 4:30, 5:23, 2:56, 4:34, 3:45, 4:12\nformats : mp3, mp4\n/\n" }, { "role": "user", "content": "How many different bike ids are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: bike_id.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT bike_id) FROM trip" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE wine (\n\t\"No\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Winery\" TEXT, \n\t\"Appelation\" TEXT, \n\t\"State\" TEXT, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Price\" INTEGER, \n\t\"Score\" INTEGER, \n\t\"Cases\" INTEGER, \n\t\"Drink\" TEXT, \n\tFOREIGN KEY(\"Grape\") REFERENCES grapes (\"Grape\"), \n\tFOREIGN KEY(\"Appelation\") REFERENCES appellations (\"Appelation\")\n)\n/\nColumns in wine and 3 examples in each column for high cardinality columns :\nNo : 87, 56, 65\nWinery : Novy, Turnbull, Loring\nAppelation : Mendocino County, Happy Canyon of Santa Barbara, Russian River Valley\nName : Wheelhouse, Limited Release, Mother Clone\nPrice : 56, 65, 75\nScore : 87, 91, 89\nCases : NULL, 377, 575\n/\n/\nColumns in wine and all categories for low cardinality columns :\nGrape : Sauvignon Blanc, Pinot Noir, Malbec, Merlot, Petite Sirah, Syrah, Cabernet Sauvingnon, Grenache, Zinfandel\nState : California\nYear : 2006, 2008, 2009, 2007\nDrink : 2013, 2001, 2012, 2011, now, 2010\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Problems\" (\n\tproblem_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\tclosure_authorised_by_staff_id INTEGER NOT NULL, \n\treported_by_staff_id INTEGER NOT NULL, \n\tdate_problem_reported DATETIME NOT NULL, \n\tdate_problem_closed DATETIME, \n\tproblem_description VARCHAR(255), \n\tother_problem_details VARCHAR(255), \n\tPRIMARY KEY (problem_id), \n\tFOREIGN KEY(reported_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Product\" (product_id), \n\tFOREIGN KEY(closure_authorised_by_staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Problems and 3 examples in each column for high cardinality columns :\nproblem_id : 1, 13, 11\nclosure_authorised_by_staff_id : 1, 13, 2\ndate_problem_reported : 1995-05-14 08:32:56, 1988-11-07 16:09:31, 1986-11-13 07:30:55\ndate_problem_closed : 1974-09-20 13:42:19, 1997-10-18 20:09:57, 2004-06-20 01:08:25\nproblem_description : d, i, s\n/\n/\nColumns in Problems and all categories for low cardinality columns :\nproduct_id : 1, 13, 2, 5, 7, 8, 4, 6, 15\nreported_by_staff_id : 1, 13, 11, 2, 5, 7, 4, 14, 10\nother_problem_details : f, m, i, s, k, l, p, v, c\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n/\n \nCREATE TABLE airports (\n\tapid INTEGER, \n\tname TEXT NOT NULL, \n\tcity TEXT, \n\tcountry TEXT, \n\tx REAL, \n\ty REAL, \n\televation BIGINT, \n\tiata TEXT(3), \n\ticao TEXT(4), \n\tPRIMARY KEY (apid)\n)\n/\nColumns in airports and 3 examples in each column for high cardinality columns :\napid : 87, 56, 65\nname : Rouyn Noranda Airport, Edmonton International Airport, Val-d'Or Airport\ncity : Medicine Hat, Sarnia, Fort Saint John\nx : -117.4469985961914, -122.054000854, -135.067001343\ny : 45.5175018311, 50.29029846191406, 47.697400654599996\nelevation : 87, 586, 56\niata : NULL, YYE, YXJ\nicao : CYXD, CYBK, CYMO\n/\n/\nColumns in airports and all categories for low cardinality columns :\ncountry : Iceland, Papua New Guinea, Greenland, Canada\n/\n \nCREATE TABLE \"Documents_Mailed\" (\n\tdocument_id INTEGER NOT NULL, \n\tmailed_to_address_id INTEGER NOT NULL, \n\tmailing_date DATETIME, \n\tPRIMARY KEY (document_id, mailed_to_address_id), \n\tFOREIGN KEY(document_id) REFERENCES \"Documents\" (document_id), \n\tFOREIGN KEY(mailed_to_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Documents_Mailed and 3 examples in each column for high cardinality columns :\nmailing_date : 2007-01-01 22:32:11, 2007-03-20 05:22:01, 1992-11-07 15:03:41\n/\n/\nColumns in Documents_Mailed and all categories for low cardinality columns :\ndocument_id : 13, 20, 2, 7, 24, 23, 4, 12, 14, 10\nmailed_to_address_id : 2, 5, 7, 8, 4, 3, 9, 0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What is the number of distinct cities the stations are located at?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT city) FROM station" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n/\n/\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n/\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER NOT NULL, \n\tparent_organization_id INTEGER, \n\torganization_details VARCHAR(255), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 7, 8, 10\nparent_organization_id : 7, 8\norganization_details : Denesik and Sons Party, Reinger, Hudson and Nolan Group, Robel-Schulist Group\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n/\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n/\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Shop_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Open_Date\" TEXT, \n\t\"Open_Year\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/\nColumns in shop and 3 examples in each column for high cardinality columns :\nShop_ID : 1, 11, 2\nShop_Name : Pentre store, Best Buy, Apple\nOpen_Date : 24 February, 18 February, 1 January\n/\n/\nColumns in shop and all categories for low cardinality columns :\nLocation : Maerdy, Porth, Blaenllechau, Pentre, Penygraig, Gelli, Dinas, Wattstown, Cymmer\nOpen_Year : 2009, 2013, 2015, 2017, 2006, 2011, 2014, 2010, 2007\n/\n \nCREATE TABLE \"PlaylistTrack\" (\n\t\"PlaylistId\" INTEGER NOT NULL, \n\t\"TrackId\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"PlaylistId\", \"TrackId\"), \n\tFOREIGN KEY(\"TrackId\") REFERENCES \"Track\" (\"TrackId\"), \n\tFOREIGN KEY(\"PlaylistId\") REFERENCES \"Playlist\" (\"PlaylistId\")\n)\n/\nColumns in PlaylistTrack and 3 examples in each column for high cardinality columns :\nTrackId : 53, 56, 65\n/\n/\nColumns in PlaylistTrack and all categories for low cardinality columns :\nPlaylistId : 1, 16, 5, 8, 17\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n \nCREATE TABLE files (\n\tf_id NUMERIC(10) NOT NULL, \n\tartist_name TEXT(50), \n\tfile_size TEXT(20), \n\tduration TEXT(20), \n\tformats TEXT(20), \n\tPRIMARY KEY (f_id), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE\n)\n/\nColumns in files and all categories for low cardinality columns :\nf_id : 1.0000000000, 5.0000000000, 6.0000000000, 3.0000000000, 2.0000000000, 4.0000000000\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\nfile_size : 4.58 MB, 5.10 MB, 4.10 MB, 3.69 MB, 3.78 MB, 4.12 MB\nduration : 4:30, 5:23, 2:56, 4:34, 3:45, 4:12\nformats : mp3, mp4\n/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n" }, { "role": "user", "content": "How many different cities have these stations?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT city) FROM station" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n/\n/\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE record (\n\t\"ID\" INTEGER, \n\t\"Result\" TEXT, \n\t\"Swimmer_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\tPRIMARY KEY (\"Swimmer_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Swimmer_ID\") REFERENCES swimmer (\"ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"ID\")\n)\n/\nColumns in record and 3 examples in each column for high cardinality columns :\nID : 1, 13, 11\n/\n/\nColumns in record and all categories for low cardinality columns :\nResult : Loss, Win, NC\nSwimmer_ID : 1, 2, 5, 4, 6, 3\nEvent_ID : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n/\n/\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n/\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n/\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n/\n/\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n/\n \nCREATE TABLE repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Counties_Represented\" TEXT, \n\t\"District\" INTEGER, \n\t\"Delegate\" TEXT, \n\t\"Party\" INTEGER, \n\t\"First_Elected\" REAL, \n\t\"Committee\" TEXT, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"District\") REFERENCES county (\"County_Id\"), \n\tFOREIGN KEY(\"Party\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 7, 8, 4, 6, 3\nCounties_Represented : 09.1 9A, 13, 12.1 12A, 12.2 12B\nDistrict : 1, 2, 4, 3\nDelegate : Miller, Warren E. Warren E. Miller, Bobo, Elizabeth Elizabeth Bobo, Pendergrass, Shane E. Shane Pendergrass, Bates, Gail H. Gail H. Bates, DeBoy, Steven J. Sr. Steven J. DeBoy, Sr., Guzzone, Guy Guy Guzzone, Turner, Frank S. Frank S. Turner, Malone, James E. Jr. James E. Malone, Jr.\nParty : 1, 2, 7, 4, 3\nFirst_Elected : 2002.0, 2006.0, 1994.0, 2003.0\nCommittee : Environmental Matters, Economic Matters, Ways and Means, Environmental Matters (Vice-Chair), Health and Government Operations, Appropriations\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n" }, { "role": "user", "content": "How many stations does Mountain View city has?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, Mountain View.\nThe SQL query I'll be generating is:\nSELECT COUNT(*) FROM station WHERE city = \"Mountain View\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE affected_region (\n\t\"Region_id\" INTEGER, \n\t\"Storm_ID\" INTEGER, \n\t\"Number_city_affected\" REAL, \n\tPRIMARY KEY (\"Region_id\", \"Storm_ID\"), \n\tFOREIGN KEY(\"Storm_ID\") REFERENCES storm (\"Storm_ID\"), \n\tFOREIGN KEY(\"Region_id\") REFERENCES region (\"Region_id\")\n)\n/\nColumns in affected_region and all categories for low cardinality columns :\nRegion_id : 1, 2, 12, 3\nStorm_ID : 1, 5, 4, 3\nNumber_city_affected : 12.0, 30.0, 15.0, 10.0, 22.0, 37.0\n/\n \nCREATE TABLE college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE \"Residents\" (\n\tresident_id INTEGER NOT NULL, \n\tproperty_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME NOT NULL, \n\tdate_moved_out DATETIME NOT NULL, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (resident_id, property_id, date_moved_in), \n\tFOREIGN KEY(property_id) REFERENCES \"Properties\" (property_id)\n)\n/\nColumns in Residents and 3 examples in each column for high cardinality columns :\nresident_id : 87, 38, 37\nproperty_id : 954, 120, 108\ndate_moved_out : 2018-01-28 13:19:54, 2017-11-14 06:28:48, 2018-02-22 06:24:15\nother_details : Anderson Batz, Jacques Glover II, Jess Wyman\n/\n/\nColumns in Residents and all categories for low cardinality columns :\ndate_moved_in : 2016-09-27 12:00:00, 2017-06-17 15:43:33, 2015-03-27 12:00:00\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n/\n/\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n/\n \nCREATE TABLE \"Participates_in\" (\n\tstuid INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Participates_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE \"Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_Type_Code\" CHAR(15) NOT NULL, \n\t\"Start_Date\" DATETIME, \n\t\"End_Date\" DATETIME, \n\tPRIMARY KEY (\"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\")\n)\n/\nColumns in Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 703, 151, 768\nStart_Date : 2018-03-13 12:30:19, 2018-02-10 08:56:30, 2018-07-21 10:36:53\nEnd_Date : 2017-10-07 08:29:25, 2018-01-19 22:45:33, 2018-03-07 13:52:47\n/\n/\nColumns in Policies and all categories for low cardinality columns :\nCustomer_ID : 588, 858, 808, 334, 252, 994, 380, 430, 857, 435\nPolicy_Type_Code : Uniformed, Normal, Jurisdiction, Deputy\n/\n \nCREATE TABLE \"Tourist_Attractions\" (\n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Attraction_Type_Code\" CHAR(15) NOT NULL, \n\t\"Location_ID\" INTEGER NOT NULL, \n\t\"How_to_Get_There\" VARCHAR(255), \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Opening_Hours\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Tourist_Attraction_ID\"), \n\tFOREIGN KEY(\"Location_ID\") REFERENCES \"Locations\" (\"Location_ID\"), \n\tFOREIGN KEY(\"Attraction_Type_Code\") REFERENCES \"Ref_Attraction_Types\" (\"Attraction_Type_Code\")\n)\n/\nColumns in Tourist_Attractions and 3 examples in each column for high cardinality columns :\nTourist_Attraction_ID : 5076, 6653, 8429\nName : film festival, flying elephant, fun shops\n/\n/\nColumns in Tourist_Attractions and all categories for low cardinality columns :\nAttraction_Type_Code : 2, 5, 6, 3, 9\nLocation_ID : 867, 858, 759, 603, 417, 661, 655, 579, 868\nHow_to_Get_There : shuttle, bus, walk\nDescription : None\nOpening_Hours : None\nOther_Details : None\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weekly_weather (\n\tstation_id INTEGER, \n\tday_of_week TEXT, \n\thigh_temperature INTEGER, \n\tlow_temperature INTEGER, \n\tprecipitation REAL, \n\twind_speed_mph INTEGER, \n\tPRIMARY KEY (station_id, day_of_week), \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in weekly_weather and 3 examples in each column for high cardinality columns :\nwind_speed_mph : 13, 20, 7\n/\n/\nColumns in weekly_weather and all categories for low cardinality columns :\nstation_id : 1, 2, 4, 3, 10\nday_of_week : Sunday, Wednesday, Tuesday, Thursday, Monday, Friday, Saturday\nhigh_temperature : 55, 49, 58, 50, 66, 59, 60, 57, 54\nlow_temperature : 56, 46, 55, 49, 50, 52, 54\nprecipitation : 60.0, 30.0, 10.0, 90.0, 50.0, 70.0, 80.0, 20.0\n/\n \nCREATE TABLE \"Claims_Processing\" (\n\t\"Claim_Processing_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Claim_Outcome_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Staff_ID\" INTEGER, \n\tPRIMARY KEY (\"Claim_Processing_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Processing and 3 examples in each column for high cardinality columns :\nClaim_Processing_ID : 243, 342, 818\n/\n/\nColumns in Claims_Processing and all categories for low cardinality columns :\nClaim_ID : 45, 28, 90, 24, 34, 62, 15, 27, 81\nClaim_Outcome_Code : Settled, In progress, Disputed\nClaim_Stage_ID : 1, 3\nStaff_ID : 771, 427, 510, 673, 986, 687, 822, 589, 718\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Country\" (\n\tid INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Country and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\nname : Scotland, Italy, Spain\n/\n\n" }, { "role": "user", "content": "How many stations are in Mountain View?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, Mountain View.\nThe SQL query I'll be generating is:\nSELECT COUNT(*) FROM station WHERE city = \"Mountain View\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER, \n\tservice_type_code VARCHAR(15) NOT NULL, \n\tservice_name VARCHAR(80), \n\tservice_descriptio VARCHAR(255), \n\tPRIMARY KEY (service_id)\n)\n/\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 1, 13, 11\n/\n/\nColumns in Services and all categories for low cardinality columns :\nservice_type_code : Welfare, Health, Education\nservice_name : Welfare, Health, Education\nservice_descriptio : Welfare, Health, Education\n/\n \nCREATE TABLE swimmer (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Nationality\" TEXT, \n\tmeter_100 REAL, \n\tmeter_200 TEXT, \n\tmeter_300 TEXT, \n\tmeter_400 TEXT, \n\tmeter_500 TEXT, \n\tmeter_600 TEXT, \n\tmeter_700 TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"ID\")\n)\n/\nColumns in swimmer and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3\nname : Przemysław Stańczyk, Grant Hackett, Federico Colbertaldo, Sébastien Rouault, Craig Stevens, Sergiy Fesenko, Oussama Mellouli, Ryan Cochrane\nNationality : Italy, Canada, Australia, Ukraine, France, Tunisia, Poland\nmeter_100 : 57.35, 57.31, 55.67, 57.84, 57.66, 57.34\nmeter_200 : 1:57.21, 1:54.40, 1:57.26, 1:57.10, 1:56.44, 1:56.34, 1:56.77\nmeter_300 : 2:56.64, 2:56.95, 2:57.10, 2:55.94, 2:53.46, 2:55.90, 2:56.02, 2:56.04\nmeter_400 : 3:55.72, 3:55.49, 3:55.36, 3:57.00, 3:52.93, 3:56.34, 3:57.12, 3:55.37\nmeter_500 : 4:54.48, 4:56.96, 4:55.08, 4:54.21, 4:54.19, 4:52.85, 4:57.03, 4:56.15\nmeter_600 : 5:54.45, 5:53.03, 5:52.92, 5:56.99, 5:56.31, 5:53.53, 5:57.10, 5:52.59\nmeter_700 : 6:55.07, 6:57.44, 6:50.91, 6:53.34, 6:52.58, 6:57.69, 6:50.80, 6:52.69\nTime : 7:55.39, 7:52.04, 7:47.91, 7:53.43, 7:46.95, 7:56.56, 7:48.67, 7:49.98\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tpayment_method_code VARCHAR(15), \n\tcustomer_number VARCHAR(20), \n\tcustomer_name VARCHAR(80), \n\tcustomer_address VARCHAR(255), \n\tcustomer_phone VARCHAR(80), \n\tcustomer_email VARCHAR(80), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_number : 586, 838, 233\ncustomer_name : Ottilie, Brenna, Madaline\ncustomer_address : 440 Aiden Ports, 058 Ben Street Apt. 034, 251 Botsford Harbors Suite 399\ncustomer_phone : 529.148.1926, 672-559-0630x7875, 479-171-6355x66065\ncustomer_email : vandervort.helena@example.org, macy.huel@example.org, dbeahan@example.net\n/\n/\nColumns in Customers and all categories for low cardinality columns :\npayment_method_code : Credit Card, Direct Debit\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Has_amenity\" (\n\tdormid INTEGER, \n\tamenid INTEGER, \n\tFOREIGN KEY(amenid) REFERENCES \"Dorm_amenity\" (amenid), \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid)\n)\n/\nColumns in Has_amenity and 3 examples in each column for high cardinality columns :\namenid : 902, 955, 930\n/\n/\nColumns in Has_amenity and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Event_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Service_ID\") REFERENCES \"Services\" (\"Service_ID\")\n)\n/\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n/\n/\nColumns in Events and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nEvent_Details : Fail, Success\n/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n/\n/\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n/\n \nCREATE TABLE debate (\n\t\"Debate_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Debate_ID\")\n)\n/\nColumns in debate and all categories for low cardinality columns :\nDebate_ID : 1, 2, 5, 4, 6, 3\nDate : October 21, 2011, December 17, 2014, August 3, 2015, January 21, 2017, October 27, 2015, January 12, 2017\nVenue : Abu Dhabi , UAE, Doha , Qatar, Dubai , UAE, Manama , Bahrain\nNum_of_Audience : 342, 159, 90, 209, 313, 134\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\n\n" }, { "role": "user", "content": "Return the unique name for stations that have ever had 7 bikes available." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, status.bikes_available.\nThe SQL query I'll be generating is:\nSELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Papers\" (\n\t\"paperID\" INTEGER, \n\ttitle TEXT, \n\tPRIMARY KEY (\"paperID\")\n)\n/\nColumns in Papers and all categories for low cardinality columns :\npaperID : 201, 204, 205, 200, 206, 203, 202\ntitle : Nameless, Painless, Binders Unbound, Proving the Unique Fixed-Point Principle Correct: An Adventure with Category Theory, An Equivalence-Preserving CPS Translation via Multi-Language Semantics, Making Standard ML a Practical Database Programming Language, Functional Pearl: Modular Rollback through Control Logging, Just do it: Simple Monadic Equational Reasoning\n/\n \nCREATE TABLE departments (\n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT '0' NOT NULL, \n\t\"DEPARTMENT_NAME\" VARCHAR(30) NOT NULL, \n\t\"MANAGER_ID\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"LOCATION_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"DEPARTMENT_ID\")\n)\n/\nColumns in departments and 3 examples in each column for high cardinality columns :\nDEPARTMENT_ID : 170, 160, 120\nDEPARTMENT_NAME : Shipping, Purchasing, Corporate Tax\nMANAGER_ID : 114, 201, 108\n/\n/\nColumns in departments and all categories for low cardinality columns :\nLOCATION_ID : 1700, 1800, 2700, 2400, 2500, 1500, 1400\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n/\n \nCREATE TABLE dept_locations (\n\t\"Dnumber\" INTEGER, \n\t\"Dlocation\" TEXT, \n\tPRIMARY KEY (\"Dnumber\", \"Dlocation\")\n)\n/\nColumns in dept_locations and all categories for low cardinality columns :\nDnumber : 1, 4, 5\nDlocation : Stafford, Sugarland, Bellaire, Houston\n/\n \nCREATE TABLE broadcast (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Time_of_day\" TEXT, \n\tPRIMARY KEY (\"Channel_ID\", \"Program_ID\"), \n\tFOREIGN KEY(\"Program_ID\") REFERENCES program (\"Program_ID\"), \n\tFOREIGN KEY(\"Channel_ID\") REFERENCES channel (\"Channel_ID\")\n)\n/\nColumns in broadcast and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nProgram_ID : 1, 2, 4, 3\nTime_of_day : Morning, Night, Noon\n/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n/\n/\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n/\n \nCREATE TABLE \"Tourist_Attractions\" (\n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Attraction_Type_Code\" CHAR(15) NOT NULL, \n\t\"Location_ID\" INTEGER NOT NULL, \n\t\"How_to_Get_There\" VARCHAR(255), \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Opening_Hours\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Tourist_Attraction_ID\"), \n\tFOREIGN KEY(\"Location_ID\") REFERENCES \"Locations\" (\"Location_ID\"), \n\tFOREIGN KEY(\"Attraction_Type_Code\") REFERENCES \"Ref_Attraction_Types\" (\"Attraction_Type_Code\")\n)\n/\nColumns in Tourist_Attractions and 3 examples in each column for high cardinality columns :\nTourist_Attraction_ID : 5076, 6653, 8429\nName : film festival, flying elephant, fun shops\n/\n/\nColumns in Tourist_Attractions and all categories for low cardinality columns :\nAttraction_Type_Code : 2, 5, 6, 3, 9\nLocation_ID : 867, 858, 759, 603, 417, 661, 655, 579, 868\nHow_to_Get_There : shuttle, bus, walk\nDescription : None\nOpening_Hours : None\nOther_Details : None\n/\n \nCREATE TABLE \"COURSE\" (\n\t\"CRS_CODE\" VARCHAR(10), \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"CRS_DESCRIPTION\" VARCHAR(35), \n\t\"CRS_CREDIT\" FLOAT, \n\tPRIMARY KEY (\"CRS_CODE\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/\nColumns in COURSE and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nDEPT_CODE : CIS, ACCT\nCRS_DESCRIPTION : Statistical Applications, Accounting I, Accounting II, Database Design and Implementation, Intro. to Microcomputing, Intro. to Statistics\nCRS_CREDIT : 3.0, 4.0\n/\n \nCREATE TABLE \"Circulation_History\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tcopy_number INTEGER NOT NULL, \n\temployee_id INTEGER NOT NULL, \n\tPRIMARY KEY (document_id, draft_number, copy_number, employee_id), \n\tFOREIGN KEY(document_id, draft_number, copy_number) REFERENCES \"Draft_Copies\" (document_id, draft_number, copy_number), \n\tFOREIGN KEY(employee_id) REFERENCES \"Employees\" (employee_id)\n)\n/\nColumns in Circulation_History and all categories for low cardinality columns :\ndocument_id : 1, 10, 2, 20\ndraft_number : 1, 2, 17, 20\ncopy_number : 10, 15, 4, 5\nemployee_id : 1, 8, 2\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Transactions_Lots\" (\n\ttransaction_id INTEGER NOT NULL, \n\tlot_id INTEGER NOT NULL, \n\tFOREIGN KEY(transaction_id) REFERENCES \"Transactions\" (transaction_id), \n\tFOREIGN KEY(lot_id) REFERENCES \"Lots\" (lot_id)\n)\n/\nColumns in Transactions_Lots and all categories for low cardinality columns :\ntransaction_id : 1, 2, 15, 7, 6, 12, 3, 14, 10\nlot_id : 1, 11, 15, 8, 4, 14, 3, 10, 9\n/\n \nCREATE TABLE player_coach (\n\t\"Player_ID\" INTEGER, \n\t\"Coach_ID\" INTEGER, \n\t\"Starting_year\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\", \"Coach_ID\"), \n\tFOREIGN KEY(\"Coach_ID\") REFERENCES coach (\"Coach_ID\"), \n\tFOREIGN KEY(\"Player_ID\") REFERENCES player (\"Player_ID\")\n)\n/\nColumns in player_coach and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 4, 6, 14, 3, 10\nCoach_ID : 1, 2, 5, 3\nStarting_year : 2012, 2010, 2011, 2013\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n/\n/\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n/\n" }, { "role": "user", "content": "What are the different names for each station that has ever had 7 bikes available?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, status.bikes_available.\nThe SQL query I'll be generating is:\nSELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station_company (\n\t\"Station_ID\" INTEGER, \n\t\"Company_ID\" INTEGER, \n\t\"Rank_of_the_Year\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\", \"Company_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES gas_station (\"Station_ID\")\n)\n/\nColumns in station_company and all categories for low cardinality columns :\nStation_ID : 1, 11, 7, 4, 6, 10\nCompany_ID : 1, 6, 3, 10, 9\nRank_of_the_Year : 1, 13, 2, 4, 3, 9\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Customers\" (\n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Customer_name\" VARCHAR(40), \n\tPRIMARY KEY (\"Customer_ID\")\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\nCustomer_ID : 756, 882, 562\nCustomer_name : Miss Felicita Reichel, Selena Gerhold, Mrs. Liza Heller V\n/\n\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\tname TEXT, \n\t\"Position\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Apps\" REAL, \n\t\"Tries\" REAL, \n\t\"Goals\" TEXT, \n\t\"Points\" REAL, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nname : Michael Platt, Tame Tupou, Terry Newton\nApps : 30.0, 29.0, 24.0\n/\n/\nColumns in player and all categories for low cardinality columns :\nPosition : Scrum Half, Right Centre, Prop, Loose Forward, Hooker, Right Wing, Stand Off, Second Row, Left Wing, Full Back\nClub_ID : 1, 2, 5, 4, 3\nTries : 3.0, 8.0, 1.0, 6.0, 9.0, 2.0, 4.0, 5.0\nGoals : 50/60, 90/106, 0/1, 0\nPoints : 36.0, 8.0, 16.0, 12.0, 24.0, 188.0, 32.0, 110.0, 4.0, 20.0\n/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE exhibition (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\t\"Ticket_Price\" REAL, \n\tPRIMARY KEY (\"Exhibition_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/\nColumns in exhibition and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2009, 2005, 2008, 2006, 2007\nTheme : Christmas Tree, Santa Claus and Rudolph the Red-Nosed Reindeer, Summer, Christmas stocking, Spring, Santa Claus\nArtist_ID : 1, 2, 4, 6, 3\nTicket_Price : 19.95, 9.95, 29.95, 14.95, 16.95\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Event_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Service_ID\") REFERENCES \"Services\" (\"Service_ID\")\n)\n/\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n/\n/\nColumns in Events and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nEvent_Details : Fail, Success\n/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n/\n/\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE schedule (\n\t\"Cinema_ID\" INTEGER, \n\t\"Film_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Show_times_per_day\" INTEGER, \n\t\"Price\" FLOAT, \n\tPRIMARY KEY (\"Cinema_ID\", \"Film_ID\"), \n\tFOREIGN KEY(\"Cinema_ID\") REFERENCES cinema (\"Cinema_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\")\n)\n/\nColumns in schedule and all categories for low cardinality columns :\nCinema_ID : 1, 2, 6, 10, 9\nFilm_ID : 1, 2, 5, 4, 3\nDate : 20 May, 2 Aug, 11 July, 21 May, 19 May, 21 Jun\nShow_times_per_day : 2, 5, 4, 3\nPrice : 9.99, 8.99, 12.99, 15.99\n/\n" }, { "role": "user", "content": "Which start station had the most trips starting from August? Give me the name and id of the station." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, start_station_id, start_date, 8/%.\nThe SQL query I'll be generating is:\nSELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE \"8/%\" GROUP BY start_station_name ORDER BY COUNT() DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE church (\n\t\"Church_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Organized_by\" TEXT, \n\t\"Open_Date\" INTEGER, \n\t\"Continuation_of\" TEXT, \n\tPRIMARY KEY (\"Church_ID\")\n)\n/\nColumns in church and all categories for low cardinality columns :\nChurch_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Pure Church of Christ, True Church of Jesus Christ of Latter Day Saints, Alston Church, Church of Christ, Church of Jesus Christ, the Bride, the Lamb's Wife, Church of Christ (Parrishite), Independent Church\nOrganized_by : Hiram Page, George M. Hinkle, Isaac Russell, Wycam Clark, Ezra Booth, William Chubby, William Law, – Hoton, Warren Parrish\nOpen_Date : 1840, 1839, 1836, 1832, 1837, 1844, 1831, 1830, 1842\nContinuation_of : Church of Jesus Christ of Latter Day Saints, Church of Christ, Church of the Latter Day Saints\n/\n \nCREATE TABLE accelerator_compatible_browser (\n\taccelerator_id INTEGER, \n\tbrowser_id INTEGER, \n\tcompatible_since_year INTEGER, \n\tPRIMARY KEY (accelerator_id, browser_id), \n\tFOREIGN KEY(browser_id) REFERENCES browser (id), \n\tFOREIGN KEY(accelerator_id) REFERENCES \"Web_client_accelerator\" (id)\n)\n/\nColumns in accelerator_compatible_browser and all categories for low cardinality columns :\naccelerator_id : 1, 2, 4, 3, 9\nbrowser_id : 1, 2, 4, 3\ncompatible_since_year : 2009, 2005, 1995, 2008, 2000, 1996, 2010, 2007\n/\n \nCREATE TABLE medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Restaurant_Type\" (\n\t\"ResTypeID\" INTEGER, \n\t\"ResTypeName\" VARCHAR(40), \n\t\"ResTypeDescription\" VARCHAR(100), \n\tPRIMARY KEY (\"ResTypeID\")\n)\n/\nColumns in Restaurant_Type and all categories for low cardinality columns :\nResTypeID : 1, 2\nResTypeName : Sandwich, Stir-fry\nResTypeDescription : Classic Chinese cooking., Simplest there is.\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Ref_Transaction_Types\" (\n\ttransaction_type_code VARCHAR(10), \n\ttransaction_type_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (transaction_type_code)\n)\n/\nColumns in Ref_Transaction_Types and all categories for low cardinality columns :\ntransaction_type_code : PUR, SALE\ntransaction_type_description : Sale, Purchase\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_quantity VARCHAR(80), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\norder_id : 13, 11, 5\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 13, 11, 2, 5, 4, 6, 12, 3, 15, 9\norder_quantity : 2, 5, 7, 8, 4, 3, 9, male\n/\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n/\n \nCREATE TABLE airlines (\n\talid INTEGER, \n\tname TEXT, \n\tiata VARCHAR(2), \n\ticao VARCHAR(3), \n\tcallsign TEXT, \n\tcountry TEXT, \n\tactive VARCHAR(2), \n\tPRIMARY KEY (alid)\n)\n/\nColumns in airlines and 3 examples in each column for high cardinality columns :\nalid : 87, 56, 65\nname : Arab Agricultural Aviation Company, Avion Taxi, Amadeus Global Travel Distribution\niata : , U3, JP\nicao : , ADP, UVS\ncallsign : , ALGOMA, SECUREX\ncountry : , Afghanistan, Gabon\n/\n/\nColumns in airlines and all categories for low cardinality columns :\nactive : Y, N\n/\n \nCREATE TABLE \"SAVINGS\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/\nColumns in SAVINGS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 4, 6, 3\nbalance : 80000.0, 230000.0, 999999999.0, 60.0, 240.0, 200000.0\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n/\n" }, { "role": "user", "content": "What are the start station's name and id for the one that had the most start trips in August?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, start_station_id, start_date, 8/%.\nThe SQL query I'll be generating is:\nSELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE \"8/%\" GROUP BY start_station_name ORDER BY COUNT(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE building (\n\tbuilding_id TEXT, \n\t\"Name\" TEXT, \n\t\"Street_address\" TEXT, \n\t\"Years_as_tallest\" TEXT, \n\t\"Height_feet\" INTEGER, \n\t\"Floors\" INTEGER, \n\tPRIMARY KEY (building_id)\n)\n/\nColumns in building and all categories for low cardinality columns :\nbuilding_id : 1, 2, 5, 7, 4, 6, 3, 0\nName : Bank of America Tower, Franklin Exchange Building, One Tampa City Center, 100 North Tampa, Park Tower, Citizens Bank Building, Floridan Hotel, Tampa City Hall\nStreet_address : 905 Franklin Street, 701 North Franklin Street, 655 North Franklin Street, 315 John F. Kennedy Boulevard, 101 East Kennedy Boulevard, 100 North Tampa Street, 400 North Tampa Street, 201 North Franklin Street\nYears_as_tallest : 1966–1972, 1981–1986, 1913–1915, 1992–present, 1986–1992, 1915–1926, 1926–1966, 1972–1981\nHeight_feet : 204, 537, 458, 577, 145, 579, 160, 280\nFloors : 42, 36, 17, 12, 39, 10, 22\n/\n \nCREATE TABLE \"CMI_Cross_References\" (\n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tmaster_customer_id INTEGER NOT NULL, \n\tsource_system_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (cmi_cross_ref_id), \n\tFOREIGN KEY(master_customer_id) REFERENCES \"Customer_Master_Index\" (master_customer_id)\n)\n/\nColumns in CMI_Cross_References and 3 examples in each column for high cardinality columns :\ncmi_cross_ref_id : 65, 75, 102\n/\n/\nColumns in CMI_Cross_References and all categories for low cardinality columns :\nmaster_customer_id : 1, 2, 5, 4, 3, 9\nsource_system_code : Rent, Electoral, Business, Parking, Tax, Benefits\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n/\n/\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n/\n \nCREATE TABLE repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(15) NOT NULL, \n\tshipping_method_code VARCHAR(15) NOT NULL, \n\torder_placed_datetime DATETIME NOT NULL, \n\torder_delivered_datetime DATETIME, \n\torder_shipping_charges VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_placed_datetime : 2009-01-18 20:06:19, 2008-10-23 06:42:10, 2009-07-05 20:02:55\norder_shipping_charges : 33.58, 77.32, 36.87\n/\n/\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 2, 5, 7, 8, 14, 12, 15, 9\norder_status_code : Paid, Delivered, Cancelled\nshipping_method_code : FedEx, UPS, Unspecified\norder_delivered_datetime : 2018-03-20 12:00:00\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n/\n \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER, \n\tservice_type_code VARCHAR(15) NOT NULL, \n\tservice_name VARCHAR(80), \n\tservice_descriptio VARCHAR(255), \n\tPRIMARY KEY (service_id)\n)\n/\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 1, 13, 11\n/\n/\nColumns in Services and all categories for low cardinality columns :\nservice_type_code : Welfare, Health, Education\nservice_name : Welfare, Health, Education\nservice_descriptio : Welfare, Health, Education\n/\n \nCREATE TABLE \"Channels\" (\n\t\"Channel_ID\" INTEGER NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/\nColumns in Channels and 3 examples in each column for high cardinality columns :\nChannel_ID : 1, 13, 11\nOther_Details : 668, 249, 943\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "Which bike traveled the most often in zip code 94002?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: bike_id, zip_code.\nThe SQL query I'll be generating is:\nSELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n/\n \nCREATE TABLE roller_coaster (\n\t\"Roller_Coaster_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Park\" TEXT, \n\t\"Country_ID\" INTEGER, \n\t\"Length\" REAL, \n\t\"Height\" REAL, \n\t\"Speed\" TEXT, \n\t\"Opened\" TEXT, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (\"Roller_Coaster_ID\"), \n\tFOREIGN KEY(\"Country_ID\") REFERENCES country (\"Country_ID\")\n)\n/\nColumns in roller_coaster and all categories for low cardinality columns :\nRoller_Coaster_ID : 1, 2, 5, 4, 6, 3\nName : The Voyage, Twister, Boardwalk Bullet, Hades 360, Dauling Dragon, Ravine Flyer II\nPark : Waldameer, Happy Valley, Mt. Olympus, Gröna Lund, Kemah Boardwalk, Holiday World\nCountry_ID : 1, 2, 3\nLength : 6442.0, 4726.0, 3236.0, 1574.0, 2900.0, 3914.0\nHeight : 96.0, 105.0, 136.0, 50.0, 120.0, 163.0\nSpeed : 67, 55, 37.9, 70, 57, 51\nOpened : May 14, 2005, 2012, August 31, 2007, 2011, May 6, 2006, May 17, 2008\nStatus : Operating\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_content VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tother_address_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_content : 92865 Margaretta Streets Suite 467, 78614 Maybell Alley Suite 057, 9443 Boyle Route Suite 857\ncity : South Meghanview, South Bellaland, Gleasonmouth\nzip_postcode : 721, 255, 416\nstate_province_county : RhodeIsland, Arizona, Mississippi\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\nother_address_details : None\n/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n/\n \nCREATE TABLE \"Block\" (\n\t\"BlockFloor\" INTEGER NOT NULL, \n\t\"BlockCode\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"BlockFloor\", \"BlockCode\")\n)\n/\nColumns in Block and all categories for low cardinality columns :\nBlockFloor : 1, 2, 4, 3\nBlockCode : 1, 2, 3\n/\n \nCREATE TABLE \"Mailshot_Campaigns\" (\n\tmailshot_id INTEGER, \n\tproduct_category VARCHAR(15), \n\tmailshot_name VARCHAR(80), \n\tmailshot_start_date DATETIME, \n\tmailshot_end_date DATETIME, \n\tPRIMARY KEY (mailshot_id)\n)\n/\nColumns in Mailshot_Campaigns and 3 examples in each column for high cardinality columns :\nmailshot_id : 17, 9, 16\nmailshot_start_date : 2017-05-20 20:05:09, 2018-02-04 13:13:36, 2017-09-27 02:35:45\nmailshot_end_date : 2018-03-15 01:06:16, 2018-03-13 14:42:26, 2018-03-01 13:42:09\n/\n/\nColumns in Mailshot_Campaigns and all categories for low cardinality columns :\nproduct_category : food, clothes\nmailshot_name : USPS, US, AL, FED\n/\n \nCREATE TABLE phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Council_Tax\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Council_Tax and all categories for low cardinality columns :\ncouncil_tax_id : 1, 2, 7, 8, 3, 9\ncmi_cross_ref_id : 106, 103, 102, 101, 104, 105\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Project_Staff\" (\n\tstaff_id DOUBLE, \n\tproject_id INTEGER NOT NULL, \n\trole_code VARCHAR(10) NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Staff_Roles\" (role_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/\nColumns in Project_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 3.0, 5137097.0, 45.0\ndate_from : 1981-10-04 22:44:50, 2000-08-28 11:49:17, 2005-01-13 11:49:48\ndate_to : 1988-03-04 19:30:05, 2004-07-28 03:11:47, 1971-07-19 22:49:05\n/\n/\nColumns in Project_Staff and all categories for low cardinality columns :\nproject_id : 1, 11, 2, 5, 7, 8, 4, 3, 15, 9\nrole_code : researcher, leader\nother_details : None\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n/\n" }, { "role": "user", "content": "What is the id of the bike that traveled the most in 94002?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: bike_id, zip_code.\nThe SQL query I'll be generating is:\nSELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Student_Course_Enrolment\" (\n\tregistration_id INTEGER, \n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_enrolment DATETIME NOT NULL, \n\tdate_of_completion DATETIME NOT NULL, \n\tPRIMARY KEY (registration_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Enrolment and 3 examples in each column for high cardinality columns :\nregistration_id : 17, 9, 16\nstudent_id : 3, 13, 11\ndate_of_enrolment : 2017-12-16 15:53:06, 2017-10-10 10:05:03, 2017-12-07 02:21:13\ndate_of_completion : 2018-03-01 07:12:39, 2018-03-22 18:04:54, 2018-03-07 09:45:48\n/\n/\nColumns in Student_Course_Enrolment and all categories for low cardinality columns :\ncourse_id : 1, 11, 2, 15, 7, 8, 4, 14, 10, 9\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15), \n\tproduct_name VARCHAR(80), \n\tproduct_price DOUBLE, \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_price : 5927021.8748021, 622.79275984494, 22956668.699482\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Hardware, Clothes\nproduct_name : Apple, jcrew, Sony, gucci\n/\n \nCREATE TABLE \"Catalogs\" (\n\tcatalog_id INTEGER, \n\tcatalog_name VARCHAR(50), \n\tcatalog_publisher VARCHAR(80), \n\tdate_of_publication DATETIME, \n\tdate_of_latest_revision DATETIME, \n\tPRIMARY KEY (catalog_id)\n)\n/\nColumns in Catalogs and all categories for low cardinality columns :\ncatalog_id : 1, 2, 5, 7, 8, 4, 6, 3\ncatalog_name : Coffee Bean, Latte, Sparkling Water, Breakfast Tea, Jam, Lemonade, Chocolate, Coco powder\ncatalog_publisher : Russel-Gislason Lemon shop, Lidl, Koepp-Rutherford handmade chocolate store, Murray Coffee shop, Grady & Kautzer\ndate_of_publication : 2012-04-13 06:37:09, 2011-07-22 04:57:19, 2013-03-15 05:09:17, 2012-11-27 19:29:22\ndate_of_latest_revision : 2017-03-30 09:15:37, 2017-10-26 01:16:51, 2017-09-26 12:10:36, 2017-12-04 06:48:13\n/\n \nCREATE TABLE channel (\n\t\"Channel_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Owner\" TEXT, \n\t\"Share_in_percent\" REAL, \n\t\"Rating_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/\nColumns in channel and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Shandong Satellite TV, CCTV-8, Hunan Satellite TV, CCTV-3, CCTV-14, CCTV-6, CCTV-13, CCTV-1, Anhui Satellite TV, CCTV-4\nOwner : HBS, Shandong Television, CCTV, Anhui Television\nShare_in_percent : 4.9, 2.33, 1.74, 2.91, 4.81, 2.6, 2.86, 3.76, 1.78, 2.73\nRating_in_percent : 0.53, 0.41, 0.32, 0.19, 0.54, 0.3, 0.31, 0.2, 0.29, 0.26\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 9590 Rogahn Point Apt. 466, 6830 Alexanne Forks Apt. 925, 319 Kozey Highway Suite 973\ncity : Edgardoberg, Gibsonfurt, Lake Floyd\nzip_postcode : 770, 116, 740\nstate_province_county : District of Columbia, Louisiana, SouthDakota\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE \"Authors\" (\n\t\"authID\" INTEGER, \n\tlname TEXT, \n\tfname TEXT, \n\tPRIMARY KEY (\"authID\")\n)\n/\nColumns in Authors and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\nlname : Gibbons, Turon, Ueno\nfname : Daniel W. H., Tim, Ralf\n/\n\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n/\n \nCREATE TABLE weekly_weather (\n\tstation_id INTEGER, \n\tday_of_week TEXT, \n\thigh_temperature INTEGER, \n\tlow_temperature INTEGER, \n\tprecipitation REAL, \n\twind_speed_mph INTEGER, \n\tPRIMARY KEY (station_id, day_of_week), \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in weekly_weather and 3 examples in each column for high cardinality columns :\nwind_speed_mph : 13, 20, 7\n/\n/\nColumns in weekly_weather and all categories for low cardinality columns :\nstation_id : 1, 2, 4, 3, 10\nday_of_week : Sunday, Wednesday, Tuesday, Thursday, Monday, Friday, Saturday\nhigh_temperature : 55, 49, 58, 50, 66, 59, 60, 57, 54\nlow_temperature : 56, 46, 55, 49, 50, 52, 54\nprecipitation : 60.0, 30.0, 10.0, 90.0, 50.0, 70.0, 80.0, 20.0\n/\n" }, { "role": "user", "content": "How many days had both mean humidity above 50 and mean visibility above 8?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: mean_humidity, mean_visibility_miles.\nThe SQL query I'll be generating is:\nSELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n/\n \nCREATE TABLE follows (\n\tf1 INTEGER NOT NULL, \n\tf2 INTEGER NOT NULL, \n\tPRIMARY KEY (f1, f2), \n\tFOREIGN KEY(f2) REFERENCES user_profiles (uid), \n\tFOREIGN KEY(f1) REFERENCES user_profiles (uid)\n)\n/\nColumns in follows and all categories for low cardinality columns :\nf1 : 1, 2, 5, 7, 3\nf2 : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Order_Items\" (\n\titem_id INTEGER NOT NULL, \n\torder_item_status_code VARCHAR(15) NOT NULL, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\titem_status_code VARCHAR(15), \n\titem_delivered_datetime DATETIME, \n\titem_order_quantity VARCHAR(80), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\nitem_id : 1, 13, 11\nitem_delivered_datetime : 2018-03-16 15:58:27, 2018-03-04 18:19:12, 2018-03-12 20:01:38\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\norder_item_status_code : Paid, Delivered, Cancelled\norder_id : 13, 11, 2, 15, 7, 8, 6, 14, 10\nproduct_id : 1, 13, 11, 5, 7, 6, 14, 3, 10, 9\nitem_status_code : good\nitem_order_quantity : 1, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Detention\" (\n\tdetention_id INTEGER, \n\tdetention_type_code VARCHAR(10) NOT NULL, \n\tteacher_id INTEGER, \n\tdatetime_detention_start DATETIME, \n\tdatetime_detention_end DATETIME, \n\tdetention_summary VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (detention_id), \n\tFOREIGN KEY(teacher_id) REFERENCES \"Teachers\" (teacher_id), \n\tFOREIGN KEY(detention_type_code) REFERENCES \"Ref_Detention_Type\" (detention_type_code)\n)\n/\nColumns in Detention and 3 examples in each column for high cardinality columns :\ndetention_id : 1, 13, 11\ndatetime_detention_start : 2017-09-05 00:38:25, 2018-01-29 20:43:45, 2017-08-25 12:00:46\ndatetime_detention_end : 2018-03-13 20:37:39, 2018-03-22 20:15:47, 2018-03-05 03:31:24\n/\n/\nColumns in Detention and all categories for low cardinality columns :\ndetention_type_code : LUNCH, AFTER, BREAK \nteacher_id : 11, 10, 5, 7, 8, 14, 3, 12, 15\ndetention_summary : None\nother_details : None\n/\n \nCREATE TABLE climber (\n\t\"Climber_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Time\" TEXT, \n\t\"Points\" REAL, \n\t\"Mountain_ID\" INTEGER, \n\tPRIMARY KEY (\"Climber_ID\"), \n\tFOREIGN KEY(\"Mountain_ID\") REFERENCES mountain (\"Mountain_ID\")\n)\n/\nColumns in climber and all categories for low cardinality columns :\nClimber_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Hans Luthringhauser, Charlie Freedman, Georg Auerbacher, Klaus Enders, Arseneus Butscher, Horst Owesle, Jean Claude Castella, Mick Horsepole, Siegfried Schauzu, L Currie\nCountry : West Germany, Switzerland, United Kingdom\nTime : 1:17.22.0, 1:25.02.8, 1:25.40.6, 1:27.28.8, 1:13.05.6, 1:18.14.6, 1:21.35.6, 1:17.16.0, 1:16.58.0, 1:14.56.4\nPoints : 8.0, 3.0, 12.0, 15.0, 10.0, 1.0, 6.0, 2.0, 4.0, 5.0\nMountain_ID : 1, 2, 5, 7, 3\n/\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Member_of\" (\n\t\"FacID\" INTEGER, \n\t\"DNO\" INTEGER, \n\t\"Appt_Type\" VARCHAR(15), \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Member_of and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\n/\n/\nColumns in Member_of and all categories for low cardinality columns :\nDNO : 50, 550, 520, 600\nAppt_Type : Secondary, Primary\n/\n \nCREATE TABLE \"Ref_Product_Categories\" (\n\tproduct_category_code VARCHAR(15), \n\tproduct_category_description VARCHAR(80), \n\tunit_of_measure VARCHAR(20), \n\tPRIMARY KEY (product_category_code)\n)\n/\nColumns in Ref_Product_Categories and all categories for low cardinality columns :\nproduct_category_code : Spices, Seeds, Herbs\nproduct_category_description : Spices, Seeds, Herbs\nunit_of_measure : Weight - pound,kilo., Handful \n/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : FM, PT, PP, CV, BK\nDocument_Type_Name : Book, Presentation, Paper, Film, CV\nDocument_Type_Description : fun, excellent, very good, good\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n/\n/\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Studio\" TEXT, \n\t\"Director\" TEXT, \n\t\"Gross_in_dollar\" INTEGER, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and 3 examples in each column for high cardinality columns :\nFilm_ID : 1, 13, 11\nTitle : Annie, Rocky III, Tootsie\nDirector : Richard Attenborough, Nicholas Meyer, Ted Kotcheff\nGross_in_dollar : 53977250, 76606280, 125049125\n/\n/\nColumns in film and all categories for low cardinality columns :\nStudio : MGM, United Artists, Universal, 20th Century Fox, Columbia, Paramount, Columbia / Rastar, Paramount / Lorimar, Orion / Carolco, Universal / RKO\n/\n \nCREATE TABLE repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\n" }, { "role": "user", "content": "What is the number of days that had an average humity above 50 and an average visibility above 8?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: mean_humidity, mean_visibility_miles.\nThe SQL query I'll be generating is:\nSELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tcolor_code VARCHAR(15) NOT NULL, \n\tproduct_category_code VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\ttypical_buying_price VARCHAR(20), \n\ttypical_selling_price VARCHAR(20), \n\tproduct_description VARCHAR(255), \n\tother_product_details VARCHAR(255), \n\tPRIMARY KEY (product_id), \n\tFOREIGN KEY(color_code) REFERENCES \"Ref_Colors\" (color_code), \n\tFOREIGN KEY(product_category_code) REFERENCES \"Ref_Product_Categories\" (product_category_code)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : peper, cumin, chili\ntypical_buying_price : , 5.578, 503.8431967\ntypical_selling_price : , 149, 10377614.847385\nproduct_description : ut, et, vel\n/\n/\nColumns in Products and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 4, 9\nproduct_category_code : Spices, Seeds, Herbs\nother_product_details : None\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE farm (\n\t\"Farm_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Total_Horses\" REAL, \n\t\"Working_Horses\" REAL, \n\t\"Total_Cattle\" REAL, \n\t\"Oxen\" REAL, \n\t\"Bulls\" REAL, \n\t\"Cows\" REAL, \n\t\"Pigs\" REAL, \n\t\"Sheep_and_Goats\" REAL, \n\tPRIMARY KEY (\"Farm_ID\")\n)\n/\nColumns in farm and all categories for low cardinality columns :\nFarm_ID : 1, 2, 5, 7, 8, 4, 6, 3\nYear : 1932, 1928, 1930, 1931, 1927, 1934, 1929, 1933\nTotal_Horses : 3658.9, 5056.5, 2546.9, 5607.5, 4781.3, 5308.2, 5486.9, 2604.8\nWorking_Horses : 3721.6, 3711.2, 3900.1, 3711.6, 4090.5, 4198.8, 2197.3, 3593.7\nTotal_Cattle : 6274.1, 4446.3, 6189.5, 8374.5, 5277.5, 7611.0, 5006.7, 8604.8\nOxen : 805.5, 895.3, 156.5, 593.7, 116.9, 113.8, 254.8, 105.2\nBulls : 49.6, 71.6, 40.0, 26.9, 32.8, 31.6, 37.6, 46.7\nCows : 3852.1, 2739.5, 2518.0, 2407.2, 3377.0, 3987.0, 3873.0, 3471.6\nPigs : 3171.8, 4236.7, 4161.2, 2089.2, 4412.4, 3373.3, 6962.9, 2623.7\nSheep_and_Goats : 7956.3, 7030.8, 2197.1, 2004.7, 3364.8, 4533.4, 2109.5, 8112.2\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Ref_Colors\" (\n\tcolor_code VARCHAR(15), \n\tcolor_description VARCHAR(80), \n\tPRIMARY KEY (color_code)\n)\n/\nColumns in Ref_Colors and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 8, 4, 3, 9\ncolor_description : blue, green, gray, red, black, yellow, purple, white\n/\n \nCREATE TABLE \"Track\" (\n\t\"TrackId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(200) NOT NULL, \n\t\"AlbumId\" INTEGER DEFAULT NULL, \n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"GenreId\" INTEGER DEFAULT NULL, \n\t\"Composer\" VARCHAR(220) DEFAULT NULL, \n\t\"Milliseconds\" INTEGER NOT NULL, \n\t\"Bytes\" INTEGER DEFAULT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"TrackId\"), \n\tFOREIGN KEY(\"MediaTypeId\") REFERENCES \"MediaType\" (\"MediaTypeId\"), \n\tFOREIGN KEY(\"GenreId\") REFERENCES \"Genre\" (\"GenreId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Album\" (\"AlbumId\")\n)\n/\nColumns in Track and 3 examples in each column for high cardinality columns :\nTrackId : 87, 56, 65\nName : Snoopy's search-Red baron, The Winner Loses, Leave My Girl Alone\nAlbumId : 17, 9, 16\nComposer : Ned Fairchild, Tony Iommi, Bill Ward, Geezer Butler, Ozzy Osbourne, Berry Gordy, Jr./Janie Bradford\nMilliseconds : 263497, 307617, 204721\nBytes : 6859518, 2301989, 6420530\n/\n/\nColumns in Track and all categories for low cardinality columns :\nMediaTypeId : 1, 2\nGenreId : 1, 2, 5, 4, 6, 3\nUnitPrice : 0.99\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE grapes (\n\t\"ID\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Color\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tUNIQUE (\"Grape\")\n)\n/\nColumns in grapes and 3 examples in each column for high cardinality columns :\nID : 17, 9, 16\nGrape : Marsanne, Tempranillo, Malbec\n/\n/\nColumns in grapes and all categories for low cardinality columns :\nColor : Red, White\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE artist (\n\tartist_name TEXT(50) NOT NULL, \n\tcountry TEXT(20), \n\tgender TEXT(20), \n\tpreferred_genre TEXT(50), \n\tCONSTRAINT a_name PRIMARY KEY (artist_name), \n\tFOREIGN KEY(preferred_genre) REFERENCES genre (g_name) ON DELETE CASCADE\n)\n/\nColumns in artist and all categories for low cardinality columns :\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\ncountry : India, UK, USA, Bangladesh\ngender : Male, Female\npreferred_genre : tagore, folk, modern, nazrul, blues, pop\n/\n \nCREATE TABLE \"Documents\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Project_ID\" INTEGER NOT NULL, \n\t\"Document_Date\" DATETIME, \n\t\"Document_Name\" VARCHAR(255), \n\t\"Document_Description\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Document_Type_Code\") REFERENCES \"Ref_Document_Types\" (\"Document_Type_Code\"), \n\tFOREIGN KEY(\"Project_ID\") REFERENCES \"Projects\" (\"Project_ID\")\n)\n/\nColumns in Documents and 3 examples in each column for high cardinality columns :\nDocument_ID : 121, 300, 240\nDocument_Date : 2007-09-26 02:39:11, 1981-11-29 10:23:01, 1970-01-30 10:53:35\nDocument_Name : Katheryn statement, Review on UK files, Noel CV\n/\n/\nColumns in Documents and all categories for low cardinality columns :\nDocument_Type_Code : FM, BK, PP, CV\nProject_ID : 195, 30, 134, 105, 35\nDocument_Description : None\nOther_Details : None\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\n/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n/\n" }, { "role": "user", "content": "What is the latitude, longitude, city of the station from which the shortest trip started?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.lat, station.long, station.city, station.id, trip.start_station_id, trip.duration.\nThe SQL query I'll be generating is:\nSELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE pilot_record (\n\t\"Record_ID\" INTEGER, \n\t\"Pilot_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\t\"Date\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\", \"Aircraft_ID\", \"Date\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Pilot_ID\") REFERENCES pilot (\"Pilot_ID\")\n)\n/\nColumns in pilot_record and all categories for low cardinality columns :\nRecord_ID : 1, 2, 5, 4, 6, 3\nPilot_ID : 1, 2, 4, 3\nAircraft_ID : 1, 2, 5, 4, 6\nDate : 2006/01/04, 2005/01/04, 2008/01/04, 2004/01/04, 2007/01/04, 2003/01/04\n/\n \nCREATE TABLE railway (\n\t\"Railway_ID\" INTEGER, \n\t\"Railway\" TEXT, \n\t\"Builder\" TEXT, \n\t\"Built\" TEXT, \n\t\"Wheels\" TEXT, \n\t\"Location\" TEXT, \n\t\"ObjectNumber\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\")\n)\n/\nColumns in railway and all categories for low cardinality columns :\nRailway_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRailway : Longmoor, LTSR, GWRWk, GERSt, GWRSn, GERHt, MR, SECR, GWRS, GNRD\nBuilder : GNR Doncaster, Stephenson, Swindon Works, GWR Swindon, GER Stratford, MR Derby, GER Hartford, SECR Ashford, Avonside\nBuilt : 1902 Midland Railway 1000 was rebuilt in 1914., 1902, 1901, 1905, 1907, 1903, 1904, 1909, 1910\nWheels : 4-4-0, 4-6-0, 0-6-0T, 4-4-2, 4-4-2T, 2-8-0, 0-6-0, 0-6-0ST\nLocation : Shildon, Swindon, Basingstoke, York, Toddington, Barrow Hill, Bressingham, Bo'ness\nObjectNumber : 1975-7005, 1978-7028, 1978-7025, 1975-7003, 1978-7026, 2008-7159, 1975-7006, 1978-7027, 1975-7018, 1976-7001\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Settlements\" (\n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Date_Claim_Made\" DATE, \n\t\"Date_Claim_Settled\" DATE, \n\t\"Amount_Claimed\" INTEGER, \n\t\"Amount_Settled\" INTEGER, \n\t\"Customer_Policy_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Settlement_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claims\" (\"Claim_ID\")\n)\n/\nColumns in Settlements and 3 examples in each column for high cardinality columns :\nSettlement_ID : 756, 616, 527\nDate_Claim_Made : 2017-05-19, 2016-09-05, 2018-05-12\nDate_Claim_Settled : 2017-12-24, 2017-11-15, 2018-02-20\nAmount_Claimed : 37302, 20569, 25078\nAmount_Settled : 1676, 1181, 930\nCustomer_Policy_ID : 943, 839, 590\n/\n/\nColumns in Settlements and all categories for low cardinality columns :\nClaim_ID : 843, 563, 801, 957, 761, 621, 486, 571, 569\n/\n \nCREATE TABLE \"Products\" (\n\t\"Product_ID\" VARCHAR(100) NOT NULL, \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\t\"Product_Description\" VARCHAR(255), \n\t\"Other_Product_Service_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Product_ID\"), \n\tUNIQUE (\"Product_ID\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nProduct_ID : 250, 300, 233\nProduct_Price : 634660.0000, 1577.0000, 900.0000\n/\n/\nColumns in Products and all categories for low cardinality columns :\nProduct_Name : dinning, photo, film\nProduct_Description : None\nOther_Product_Service_Details : None\n/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_date DATETIME, \n\tPRIMARY KEY (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 2018-03-16 21:57:43, 2018-03-20 00:21:41, 2018-03-05 08:47:33\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\norder_id : 13, 11, 5, 8, 4, 12, 3, 14, 10, 9\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n/\n" }, { "role": "user", "content": "What is the latitude, longitude, and city of the station from which the trip with smallest duration started?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.lat, station.long, station.city, station.id, trip.start_station_id, trip.duration.\nThe SQL query I'll be generating is:\nSELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n/\n/\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n/\n/\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" REAL, \n\t\"Competition_type\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\")\n)\n/\nColumns in competition and 3 examples in each column for high cardinality columns :\nCompetition_ID : 1, 11, 2\n/\n/\nColumns in competition and all categories for low cardinality columns :\nYear : 2006.0, 2007.0\nCompetition_type : Tournament, Friendly\nCountry : Italy, Slovenia, Spain, Australia, Russia, Ireland\n/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : RV, BK, PR, CV\nDocument_Type_Name : Book, Review, CV, Paper\nDocument_Type_Description : \n/\n \nCREATE TABLE \"Songs\" (\n\t\"SongId\" INTEGER, \n\t\"Title\" TEXT, \n\tPRIMARY KEY (\"SongId\")\n)\n/\nColumns in Songs and all categories for low cardinality columns :\nSongId : \nTitle : \n/\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tdate_account_opened DATETIME, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\ndate_account_opened : 2016-07-30 22:22:24, 2016-04-25 21:49:17, 2017-05-29 16:45:17\naccount_name : 601, 398, 900\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 8, 6, 12, 3, 15, 9\nother_account_details : VIP, Regular\n/\n \nCREATE TABLE discipline_enrollments (\n\t\"Campus\" INTEGER, \n\t\"Discipline\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Undergraduate\" INTEGER, \n\t\"Graduate\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Discipline\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in discipline_enrollments and 3 examples in each column for high cardinality columns :\nCampus : 1, 13, 11\nDiscipline : 19, 17, 21\nUndergraduate : 986, 65, 815\nGraduate : 56, 377, 187\n/\n/\nColumns in discipline_enrollments and all categories for low cardinality columns :\nYear : 2004\n/\n \nCREATE TABLE medicine_enzyme_interaction (\n\tenzyme_id INTEGER, \n\tmedicine_id INTEGER, \n\tinteraction_type TEXT, \n\tPRIMARY KEY (enzyme_id, medicine_id), \n\tFOREIGN KEY(medicine_id) REFERENCES medicine (id), \n\tFOREIGN KEY(enzyme_id) REFERENCES enzyme (id)\n)\n/\nColumns in medicine_enzyme_interaction and 3 examples in each column for high cardinality columns :\nmedicine_id : 1, 13, 20\n/\n/\nColumns in medicine_enzyme_interaction and all categories for low cardinality columns :\nenzyme_id : 1, 2, 5, 4, 6, 3\ninteraction_type : inhibitor, activitor\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n/\n \nCREATE TABLE useracct (\n\tu_id INTEGER NOT NULL, \n\tname VARCHAR(128) DEFAULT NULL, \n\tPRIMARY KEY (u_id)\n)\n/\nColumns in useracct and all categories for low cardinality columns :\nu_id : 1, 2, 5, 7, 4, 6, 3\nname : Rosie, Emily, Roxi, Helen, Terry, Mark, Nancy\n/\n \nCREATE TABLE artwork (\n\t\"Artwork_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\")\n)\n/\nColumns in artwork and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nType : Presenter Talent Show, Program Talent Show, Presenter Music/Variety Show, Program Music/Variety Show\nName : Why, I Know, Martin, Indonesian Idol, Loving you, Daniel Mananta, Back Home, Cats, Boys\n/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n/\n" }, { "role": "user", "content": "What are the ids of stations that are located in San Francisco and have average bike availability above 10." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, city, San Francisco, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT id FROM station WHERE city = \"San Francisco\" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n/\n \nCREATE TABLE \"Project_Staff\" (\n\tstaff_id DOUBLE, \n\tproject_id INTEGER NOT NULL, \n\trole_code VARCHAR(10) NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Staff_Roles\" (role_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/\nColumns in Project_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 3.0, 5137097.0, 45.0\ndate_from : 1981-10-04 22:44:50, 2000-08-28 11:49:17, 2005-01-13 11:49:48\ndate_to : 1988-03-04 19:30:05, 2004-07-28 03:11:47, 1971-07-19 22:49:05\n/\n/\nColumns in Project_Staff and all categories for low cardinality columns :\nproject_id : 1, 11, 2, 5, 7, 8, 4, 3, 15, 9\nrole_code : researcher, leader\nother_details : None\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n/\n \nCREATE TABLE \"Artist\" (\n\t\"ArtistId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"ArtistId\")\n)\n/\nColumns in Artist and 3 examples in each column for high cardinality columns :\nArtistId : 87, 56, 65\nName : Smashing Pumpkins, Santana Feat. Eric Clapton, Godsmack\n/\n\n \nCREATE TABLE \"Customer_Contact_Channels\" (\n\tcustomer_id INTEGER NOT NULL, \n\tchannel_code VARCHAR(15) NOT NULL, \n\tactive_from_date DATETIME NOT NULL, \n\tactive_to_date DATETIME, \n\tcontact_number VARCHAR(50) NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Contact_Channels and 3 examples in each column for high cardinality columns :\nactive_from_date : 2017-05-25 16:08:45, 2017-06-21 06:41:19, 2018-03-01 10:17:18\nactive_to_date : 2018-03-16 14:00:15, 2018-02-24 00:57:39, 2018-03-20 14:01:12\ncontact_number : 940.035.6435x0225, 846.043.4809x0426, 1-968-863-4947x96956\n/\n/\nColumns in Customer_Contact_Channels and all categories for low cardinality columns :\ncustomer_id : 13, 2, 5, 15, 4, 6, 14, 3, 10, 9\nchannel_code : Mobile, Email, Fax, Handheld, Cell\n/\n \nCREATE TABLE \"Plays_Games\" (\n\t\"StuID\" INTEGER, \n\t\"GameID\" INTEGER, \n\t\"Hours_Played\" INTEGER, \n\tFOREIGN KEY(\"GameID\") REFERENCES \"Video_Games\" (\"GameID\"), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Plays_Games and all categories for low cardinality columns :\nStuID : 1007, 1008, 1032, 1010, 1001\nGameID : 1, 2, 5, 4, 6, 3\nHours_Played : 1, 100, 10, 1000, 50, 47, 15, 1337, 35\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE prereq (\n\tcourse_id VARCHAR(8), \n\tprereq_id VARCHAR(8), \n\tPRIMARY KEY (course_id, prereq_id), \n\tFOREIGN KEY(course_id) REFERENCES course (course_id), \n\tFOREIGN KEY(prereq_id) REFERENCES course (course_id)\n)\n/\nColumns in prereq and 3 examples in each column for high cardinality columns :\ncourse_id : 241, 586, 628\nprereq_id : 304, 628, 927\n/\n\n \nCREATE TABLE \"Catalogs\" (\n\tcatalog_id INTEGER, \n\tcatalog_name VARCHAR(50), \n\tcatalog_publisher VARCHAR(80), \n\tdate_of_publication DATETIME, \n\tdate_of_latest_revision DATETIME, \n\tPRIMARY KEY (catalog_id)\n)\n/\nColumns in Catalogs and all categories for low cardinality columns :\ncatalog_id : 1, 2, 5, 7, 8, 4, 6, 3\ncatalog_name : Coffee Bean, Latte, Sparkling Water, Breakfast Tea, Jam, Lemonade, Chocolate, Coco powder\ncatalog_publisher : Russel-Gislason Lemon shop, Lidl, Koepp-Rutherford handmade chocolate store, Murray Coffee shop, Grady & Kautzer\ndate_of_publication : 2012-04-13 06:37:09, 2011-07-22 04:57:19, 2013-03-15 05:09:17, 2012-11-27 19:29:22\ndate_of_latest_revision : 2017-03-30 09:15:37, 2017-10-26 01:16:51, 2017-09-26 12:10:36, 2017-12-04 06:48:13\n/\n" }, { "role": "user", "content": "What are the ids of the stations in San Francisco that normally have more than 10 bikes available?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, city, San Francisco, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT id FROM station WHERE city = \"San Francisco\" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Photos\" (\n\t\"Photo_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Filename\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Photo_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Photos and 3 examples in each column for high cardinality columns :\nPhoto_ID : 428, 303, 332\nTourist_Attraction_ID : 5076, 6523, 5265\nName : fun3, din2, park1\nFilename : 863, 695, 392\n/\n/\nColumns in Photos and all categories for low cardinality columns :\nDescription : None\nOther_Details : None\n/\n \nCREATE TABLE \"Complaints\" (\n\tcomplaint_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tcomplaint_outcome_code VARCHAR(20) NOT NULL, \n\tcomplaint_status_code VARCHAR(20) NOT NULL, \n\tcomplaint_type_code VARCHAR(20) NOT NULL, \n\tdate_complaint_raised DATETIME, \n\tdate_complaint_closed DATETIME, \n\tstaff_id INTEGER NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Complaints and 3 examples in each column for high cardinality columns :\ncomplaint_id : 1, 11, 2\n/\n/\nColumns in Complaints and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\ncustomer_id : 120, 114, 113, 116, 117, 115, 118\ncomplaint_outcome_code : OK\ncomplaint_status_code : Open, Closed, New\ncomplaint_type_code : Product Failure, Product Unusable\ndate_complaint_raised : 2006-10-29 07:08:46, 2002-07-18 10:59:35, 1977-08-06 00:31:19, 1987-07-11 14:40:30, 1973-02-10 22:55:56, 2007-10-14 21:50:43\ndate_complaint_closed : 2013-09-14 02:59:10, 1975-10-11 05:54:30, 1970-10-14 00:57:25, 1976-04-19 11:03:06, 1995-09-11 14:48:46, 2000-08-17 17:02:48\nstaff_id : 120, 114, 116, 117, 115, 118\n/\n \nCREATE TABLE \"Customer_Payments\" (\n\tcustomer_id INTEGER NOT NULL, \n\tdatetime_payment DATETIME NOT NULL, \n\tpayment_method_code VARCHAR(10) NOT NULL, \n\tamount_payment DOUBLE, \n\tPRIMARY KEY (customer_id, datetime_payment), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Payments and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ndatetime_payment : 2018-03-20 21:38:41, 2018-02-15 16:38:49, 2018-02-19 01:49:59\namount_payment : 9570.93, 6782.84, 787.12\n/\n/\nColumns in Customer_Payments and all categories for low cardinality columns :\npayment_method_code : Direct Debit, Credit Card\n/\n \nCREATE TABLE aircraft (\n\t\"Aircraft_ID\" INTEGER NOT NULL, \n\t\"Aircraft\" VARCHAR(50) NOT NULL, \n\t\"Description\" VARCHAR(50) NOT NULL, \n\t\"Max_Gross_Weight\" VARCHAR(50) NOT NULL, \n\t\"Total_disk_area\" VARCHAR(50) NOT NULL, \n\t\"Max_disk_Loading\" VARCHAR(50) NOT NULL, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 4, 3\nAircraft : Bell 206B3 JetRanger, Mil Mi-26, CH-53E Super Stallion, Robinson R-22, CH-47D Chinook\nDescription : Light utility helicopter, Heavy-lift helicopter, Turboshaft utility helicopter, Tandem rotor helicopter\nMax_Gross_Weight : 50,000 lb (22,680 kg), 123,500 lb (56,000 kg), 73,500 lb (33,300 kg), 3,200 lb (1,451 kg), 1,370 lb (635 kg)\nTotal_disk_area : 872 ft² (81.1 m²), 5,655 ft² (526 m²), 8,495 ft² (789 m²), 497 ft² (46.2 m²), 4,900 ft² (460 m²)\nMax_disk_Loading : 15 lb/ft² (72 kg/m²), 2.6 lb/ft² (14 kg/m²), 14.5 lb/ft² (71 kg/m²), 8.8 lb/ft² (43 kg/m²), 3.7 lb/ft² (18 kg/m²)\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE county (\n\t\"County_Id\" INTEGER, \n\t\"County_name\" TEXT, \n\t\"Population\" REAL, \n\t\"Zip_code\" TEXT, \n\tPRIMARY KEY (\"County_Id\")\n)\n/\nColumns in county and all categories for low cardinality columns :\nCounty_Id : 1, 2, 5, 4, 3\nCounty_name : Baltimore County, Howard, Colony, Manning, Mansfield\nPopulation : 87200.0, 13300.0, 21000.0, 79000.0, 90000.0\nZip_code : D09, D02, D21, D11, D08\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Graduation_College\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 4, 6, 3\nAge : 37, 25, 30, 34, 27, 31\nName : Tom Sheehey, Reggie Lewis, Brad Lohaus, David Butler, Tim Naegeli, Darryl Kennedy, Jerry Corcoran\nNationality : United States, United Kindom\nGraduation_College : Wisconsin–Stevens Point, California, Virginia, Iowa, Northeastern, Oklahoma\n/\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE \"Apartments\" (\n\tapt_id INTEGER NOT NULL, \n\tbuilding_id INTEGER NOT NULL, \n\tapt_type_code CHAR(15), \n\tapt_number CHAR(10), \n\tbathroom_count INTEGER, \n\tbedroom_count INTEGER, \n\troom_count CHAR(5), \n\tPRIMARY KEY (apt_id), \n\tFOREIGN KEY(building_id) REFERENCES \"Apartment_Buildings\" (building_id), \n\tUNIQUE (apt_id)\n)\n/\nColumns in Apartments and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_number : Suite 307, Apt. 411, Apt. 585\n/\n/\nColumns in Apartments and all categories for low cardinality columns :\nbuilding_id : 153, 673, 808, 744, 624, 790, 191, 734, 225\napt_type_code : Studio, Flat, Duplex\nbathroom_count : 1, 2, 3\nbedroom_count : 5, 4, 6, 3\nroom_count : 5, 7, 8, 6, 3, 9\n/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\n\n \nCREATE TABLE artist (\n\tartist_name TEXT(50) NOT NULL, \n\tcountry TEXT(20), \n\tgender TEXT(20), \n\tpreferred_genre TEXT(50), \n\tCONSTRAINT a_name PRIMARY KEY (artist_name), \n\tFOREIGN KEY(preferred_genre) REFERENCES genre (g_name) ON DELETE CASCADE\n)\n/\nColumns in artist and all categories for low cardinality columns :\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\ncountry : India, UK, USA, Bangladesh\ngender : Male, Female\npreferred_genre : tagore, folk, modern, nazrul, blues, pop\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "What are the names and ids of stations that had more than 14 bikes available on average or were installed in December?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, status.bikes_available, name, id, installation_date, 12/%.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE \"12/%\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n/\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n/\n/\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n/\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER NOT NULL, \n\tparent_organization_id INTEGER, \n\torganization_details VARCHAR(255), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 7, 8, 10\nparent_organization_id : 7, 8\norganization_details : Denesik and Sons Party, Reinger, Hudson and Nolan Group, Robel-Schulist Group\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE constructors (\n\t\"constructorId\" INTEGER, \n\t\"constructorRef\" TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"constructorId\")\n)\n/\nColumns in constructors and 3 examples in each column for high cardinality columns :\nconstructorId : 87, 56, 65\nconstructorRef : mf1, prost, lambo\nname : McLaren, Protos, Eagle-Climax\nnationality : Mexican, Russian, British\nurl : http://en.wikipedia.org/wiki/Minardi, http://en.wikipedia.org/wiki/Officine_Specializate_Costruzione_Automobili, http://en.wikipedia.org/wiki/Scirocco-Powell\n/\n\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE game (\n\tstadium_id INTEGER, \n\tid INTEGER, \n\t\"Season\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Home_team\" TEXT, \n\t\"Away_team\" TEXT, \n\t\"Score\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(stadium_id) REFERENCES stadium (id)\n)\n/\nColumns in game and 3 examples in each column for high cardinality columns :\nstadium_id : 1, 11, 2\nid : 17, 9, 16\nDate : 30 June 2013, 18 May 2007, 8 August 2009\nScore : 0–0 (7:6), –, 1–3\n/\n/\nColumns in game and all categories for low cardinality columns :\nSeason : 2009, 2013, 2008, 2012, 2011, 2010, 2007\nHome_team : Pakhtakor, Bunyodkor, Quruvchi\nAway_team : Pakhtakor, Bunyodkor, Quruvchi\nCompetition : League, Supercup, Cup\n/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n/\n \nCREATE TABLE \"Ref_Calendar\" (\n\t\"Calendar_Date\" DATETIME NOT NULL, \n\t\"Day_Number\" INTEGER, \n\tPRIMARY KEY (\"Calendar_Date\")\n)\n/\nColumns in Ref_Calendar and 3 examples in each column for high cardinality columns :\nCalendar_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1972-03-31 09:47:22\n/\n/\nColumns in Ref_Calendar and all categories for low cardinality columns :\nDay_Number : 1, 2, 5, 7, 8, 3, 9\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE storm (\n\t\"Storm_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Dates_active\" TEXT, \n\t\"Max_speed\" INTEGER, \n\t\"Damage_millions_USD\" REAL, \n\t\"Number_Deaths\" INTEGER, \n\tPRIMARY KEY (\"Storm_ID\")\n)\n/\nColumns in storm and all categories for low cardinality columns :\nStorm_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Three, One, Five, Nine, Four, Seven, Six, Eight, 9 cyclones, Two\nDates_active : August5–August14, May19 –October26, August3–August10, September22–September28, September7–September17, May19–May25, October24–October26, August26–September2, September18–September25, October20–October24\nMax_speed : 1007, 988, 977, 961, 972, 1002, 983, 995\nDamage_millions_USD : 1.49, 10.75, 13.0, 29.3, 4.05, 0.039\nNumber_Deaths : 2, 7, 52, 3, 71, 0\n/\n \nCREATE TABLE protein (\n\tcommon_name TEXT, \n\tprotein_name TEXT, \n\tdivergence_from_human_lineage REAL, \n\taccession_number TEXT, \n\tsequence_length REAL, \n\tsequence_identity_to_human_protein TEXT, \n\t\"Institution_id\" TEXT, \n\tPRIMARY KEY (common_name), \n\tFOREIGN KEY(\"Institution_id\") REFERENCES \"Institution\" (\"Institution_id\")\n)\n/\nColumns in protein and all categories for low cardinality columns :\ncommon_name : Tropical Clawed Frog, porkworm, body louse, southern house mosquito, purple sea urchin\nprotein_name : uncharacterized protein LOC578090, conserved hypothetical protein, Centromeric protein E, putative, surface antigen repeat family protein, uncharacterized protein C20orf117-like\ndivergence_from_human_lineage : 937.5, 742.9, 782.7, 371.2\naccession_number : XP_003380263.1, XP_002942331.1, XP_783370.2, XP_002429877.1, XP_001843754.1\nsequence_length : 2030.0, 1587.0, 2086.0, 1584.0, 1878.0\nsequence_identity_to_human_protein : 30%, 47%, 36%, 39%, 32%\nInstitution_id : 1, 5, 9, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_name VARCHAR(255), \n\tgender VARCHAR(1), \n\tother_staff_details VARCHAR(255), \n\tPRIMARY KEY (staff_id)\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_name : Edmond, Audreanne, Oren\n/\n/\nColumns in Staff and all categories for low cardinality columns :\ngender : 1, 0\nother_staff_details : Woker, None, Manager\n/\n" }, { "role": "user", "content": "What are the names and ids of all stations that have more than 14 bikes available on average or had bikes installed in December?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, status.bikes_available, name, id, installation_date, 12/%.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE \"12/%\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE classroom (\n\tbuilding VARCHAR(15), \n\troom_number VARCHAR(7), \n\tcapacity NUMERIC(4, 0), \n\tPRIMARY KEY (building, room_number)\n)\n/\nColumns in classroom and 3 examples in each column for high cardinality columns :\nbuilding : Power, Bronfman, Whitman\nroom_number : 261, 375, 757\ncapacity : 65, 97, 51\n/\n\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER, \n\tdate_formed DATETIME, \n\torganization_name VARCHAR(255), \n\tuk_vat_number VARCHAR(20), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 1, 2, 5, 4, 3\ndate_formed : 2016-08-24 23:52:48, 2016-07-28 01:45:10, 2016-10-09 07:22:53, 2017-04-06 23:59:16, 2016-10-01 12:42:01\norganization_name : Liberal Democrats, Green Party, Labour Party, Conservative, Plaid Cymru\nuk_vat_number : 2157, 1211, 7459, 7237, 4271\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\n \nCREATE TABLE host (\n\t\"Host_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\tPRIMARY KEY (\"Host_ID\")\n)\n/\nColumns in host and all categories for low cardinality columns :\nHost_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Lloyd Daniels, Kornel David, Antonio Davis, Carlos Delfino, DeMar DeRozan, Ed Davis, Austin Daye, Derrick Dial, Justin Dentmon, Hubert Davis\nNationality : United States, Argentina, Hungary\nAge : 26, 45, 37, 40, 30, 60, 47, 43, 31\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE railway (\n\t\"Railway_ID\" INTEGER, \n\t\"Railway\" TEXT, \n\t\"Builder\" TEXT, \n\t\"Built\" TEXT, \n\t\"Wheels\" TEXT, \n\t\"Location\" TEXT, \n\t\"ObjectNumber\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\")\n)\n/\nColumns in railway and all categories for low cardinality columns :\nRailway_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRailway : Longmoor, LTSR, GWRWk, GERSt, GWRSn, GERHt, MR, SECR, GWRS, GNRD\nBuilder : GNR Doncaster, Stephenson, Swindon Works, GWR Swindon, GER Stratford, MR Derby, GER Hartford, SECR Ashford, Avonside\nBuilt : 1902 Midland Railway 1000 was rebuilt in 1914., 1902, 1901, 1905, 1907, 1903, 1904, 1909, 1910\nWheels : 4-4-0, 4-6-0, 0-6-0T, 4-4-2, 4-4-2T, 2-8-0, 0-6-0, 0-6-0ST\nLocation : Shildon, Swindon, Basingstoke, York, Toddington, Barrow Hill, Bressingham, Bo'ness\nObjectNumber : 1975-7005, 1978-7028, 1978-7025, 1975-7003, 1978-7026, 2008-7159, 1975-7006, 1978-7027, 1975-7018, 1976-7001\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n/\n" }, { "role": "user", "content": "What is the 3 most common cloud cover rates in the region of zip code 94107?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: cloud_cover, zip_code.\nThe SQL query I'll be generating is:\nSELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id)\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\naccount_name : 866, 725, 858\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 2, 8, 4, 6, 12, 14, 10, 9\nother_account_details : VIP, Regular\n/\n \nCREATE TABLE affected_region (\n\t\"Region_id\" INTEGER, \n\t\"Storm_ID\" INTEGER, \n\t\"Number_city_affected\" REAL, \n\tPRIMARY KEY (\"Region_id\", \"Storm_ID\"), \n\tFOREIGN KEY(\"Storm_ID\") REFERENCES storm (\"Storm_ID\"), \n\tFOREIGN KEY(\"Region_id\") REFERENCES region (\"Region_id\")\n)\n/\nColumns in affected_region and all categories for low cardinality columns :\nRegion_id : 1, 2, 12, 3\nStorm_ID : 1, 5, 4, 3\nNumber_city_affected : 12.0, 30.0, 15.0, 10.0, 22.0, 37.0\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n/\n\n \nCREATE TABLE \"Drama_Workshop_Groups\" (\n\t\"Workshop_Group_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER NOT NULL, \n\t\"Currency_Code\" CHAR(15) NOT NULL, \n\t\"Marketing_Region_Code\" CHAR(15) NOT NULL, \n\t\"Store_Name\" VARCHAR(255), \n\t\"Store_Phone\" VARCHAR(255), \n\t\"Store_Email_Address\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Workshop_Group_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tUNIQUE (\"Workshop_Group_ID\")\n)\n/\nColumns in Drama_Workshop_Groups and 3 examples in each column for high cardinality columns :\nWorkshop_Group_ID : 954, 431, 838\nAddress_ID : 230, 110, 180\nStore_Name : Hansen Print, Welch Flower, Roo Place\nStore_Phone : 492-463-5967, (256)743-0310, (636)443-4067\nStore_Email_Address : arturo.orn@example.org, bednar.michael@example.org, hansen.krista@example.net\n/\n/\nColumns in Drama_Workshop_Groups and all categories for low cardinality columns :\nCurrency_Code : EU, USD\nMarketing_Region_Code : FR, PT, MX, US, DE, IE, ES, RU\nOther_Details : Good, None, Bad\n/\n \nCREATE TABLE \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (\"Service_ID\")\n)\n/\nColumns in Services and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nService_Type_Code : Marriage, Birth Proof, Death Proof, Property Change\n/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\tprevious_transaction_id INTEGER, \n\taccount_id INTEGER NOT NULL, \n\tcard_id INTEGER NOT NULL, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DOUBLE, \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(card_id) REFERENCES \"Customers_Cards\" (card_id)\n)\n/\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\nprevious_transaction_id : 925, 947, 986\naccount_id : 1, 13, 11\ntransaction_date : 2018-03-24 10:39:09, 2018-03-23 21:59:28, 2018-03-24 05:45:57\ntransaction_amount : 486.56, 1336.21, 945.43\n/\n/\nColumns in Financial_Transactions and all categories for low cardinality columns :\ncard_id : 1, 11, 2, 5, 7, 4, 6, 12, 3, 9\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n/\n \nCREATE TABLE region (\n\t\"Region_ID\" INTEGER, \n\t\"Region_name\" TEXT, \n\t\"Date\" TEXT, \n\t\"Label\" TEXT, \n\t\"Format\" TEXT, \n\t\"Catalogue\" TEXT, \n\tPRIMARY KEY (\"Region_ID\")\n)\n/\nColumns in region and all categories for low cardinality columns :\nRegion_ID : 1, 2, 5, 4, 3\nRegion_name : Japan, United Kingdom, United States\nDate : 1 July 2002, 16 July 2002, 3 July 2002\nLabel : Toshiba-EMI, Astralwerks, Parlophone\nFormat : CD digipak, 2× LP, CD\nCatalogue : ASW 40362, ASW 40522, 539 9821, TOCP-66045, 540 3622\n/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n" }, { "role": "user", "content": "What are the 3 most common cloud covers in the zip code of 94107?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: cloud_cover, zip_code.\nThe SQL query I'll be generating is:\nSELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE regions (\n\t\"REGION_ID\" DECIMAL(5, 0) NOT NULL, \n\t\"REGION_NAME\" VARCHAR(25) DEFAULT NULL, \n\tPRIMARY KEY (\"REGION_ID\")\n)\n/\nColumns in regions and all categories for low cardinality columns :\nREGION_ID : 1, 2, 4, 3\nREGION_NAME : Europe\\r, Middle East and Africa\\r, Asia\\r, Americas\\r\n/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Reviewer\" (\n\t\"rID\" INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (\"rID\")\n)\n/\nColumns in Reviewer and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nname : Chris Jackson, Sarah Martinez, Mike Anderson, James Cameron, Elizabeth Thomas, Brittany Harris, Daniel Lewis, Ashley White\n/\n \nCREATE TABLE airlines (\n\talid INTEGER, \n\tname TEXT, \n\tiata VARCHAR(2), \n\ticao VARCHAR(3), \n\tcallsign TEXT, \n\tcountry TEXT, \n\tactive VARCHAR(2), \n\tPRIMARY KEY (alid)\n)\n/\nColumns in airlines and 3 examples in each column for high cardinality columns :\nalid : 87, 56, 65\nname : Arab Agricultural Aviation Company, Avion Taxi, Amadeus Global Travel Distribution\niata : , U3, JP\nicao : , ADP, UVS\ncallsign : , ALGOMA, SECUREX\ncountry : , Afghanistan, Gabon\n/\n/\nColumns in airlines and all categories for low cardinality columns :\nactive : Y, N\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE manager (\n\t\"Manager_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Working_year_starts\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Manager_ID\")\n)\n/\nColumns in manager and all categories for low cardinality columns :\nManager_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ben Curtis, Sandy Lyle, Todd Hamilton, David Duval, Tiger Woods, Greg Norman, Nick Faldo\nCountry : United States, Australia, Scotland, England\nWorking_year_starts : 2004, 1993, 2001, 1985, 1999, 2006, 2003\nAge : 46, 45, 55, 48, 52, 47, 51\nLevel : 11, 5, 7, 8, 12\n/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n/\n/\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id INTEGER, \n\tauthor_id INTEGER NOT NULL, \n\tsubject_id INTEGER NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tPRIMARY KEY (course_id), \n\tFOREIGN KEY(subject_id) REFERENCES \"Subjects\" (subject_id), \n\tFOREIGN KEY(author_id) REFERENCES \"Course_Authors_and_Tutors\" (author_id)\n)\n/\nColumns in Courses and 3 examples in each column for high cardinality columns :\ncourse_id : 1, 13, 11\ncourse_name : modern Arts, AI, Writing in French\ncourse_description : modern Arts, AI, Writing in French\n/\n/\nColumns in Courses and all categories for low cardinality columns :\nauthor_id : 13, 11, 5, 8, 4, 6, 14, 12, 15, 9\nsubject_id : 1, 2, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n/\n\n \nCREATE TABLE driver (\n\t\"Driver_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Home_city\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Driver_ID\")\n)\n/\nColumns in driver and 3 examples in each column for high cardinality columns :\nDriver_ID : 1, 11, 2\nName : Edwin Vargas, Henry Genga, Douglas McCrory\n/\n/\nColumns in driver and all categories for low cardinality columns :\nParty : Rep, Dem\nHome_city : Coventry, East Hartford, Hartford, Bethel, Manchester\nAge : 38, 45, 46, 37, 40, 36, 30, 52, 42, 35\n/\n \nCREATE TABLE medicine_enzyme_interaction (\n\tenzyme_id INTEGER, \n\tmedicine_id INTEGER, \n\tinteraction_type TEXT, \n\tPRIMARY KEY (enzyme_id, medicine_id), \n\tFOREIGN KEY(medicine_id) REFERENCES medicine (id), \n\tFOREIGN KEY(enzyme_id) REFERENCES enzyme (id)\n)\n/\nColumns in medicine_enzyme_interaction and 3 examples in each column for high cardinality columns :\nmedicine_id : 1, 13, 20\n/\n/\nColumns in medicine_enzyme_interaction and all categories for low cardinality columns :\nenzyme_id : 1, 2, 5, 4, 6, 3\ninteraction_type : inhibitor, activitor\n/\n \nCREATE TABLE \"Parties_in_Events\" (\n\t\"Party_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15), \n\tPRIMARY KEY (\"Party_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES \"Parties\" (\"Party_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/\nColumns in Parties_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 15\n/\n/\nColumns in Parties_in_Events and all categories for low cardinality columns :\nParty_ID : 5, 4, 6, 3, 9\nRole_Code : Organizer, Participant\n/\n \nCREATE TABLE \"Payments\" (\n\t\"Payment_ID\" INTEGER NOT NULL, \n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Payment_Method_Code\" VARCHAR(255), \n\t\"Date_Payment_Made\" DATE, \n\t\"Amount_Payment\" INTEGER, \n\tPRIMARY KEY (\"Payment_ID\"), \n\tFOREIGN KEY(\"Settlement_ID\") REFERENCES \"Settlements\" (\"Settlement_ID\")\n)\n/\nColumns in Payments and 3 examples in each column for high cardinality columns :\nPayment_ID : 754, 739, 542\nDate_Payment_Made : 2017-06-24, 2017-08-06, 2017-12-16\nAmount_Payment : 423154, 155654, 71246\n/\n/\nColumns in Payments and all categories for low cardinality columns :\nSettlement_ID : 527, 476, 564, 983, 682, 648, 597, 512, 516\nPayment_Method_Code : Visa, Discover Card, American Express, MasterCard\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What is the zip code in which the average mean sea level pressure is the lowest?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_sea_level_pressure_inches.\nThe SQL query I'll be generating is:\nSELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Ref_Service_Types\" (\n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\t\"Parent_Service_Type_Code\" CHAR(15), \n\t\"Service_Type_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Service_Type_Code\"), \n\tUNIQUE (\"Service_Type_Code\")\n)\n/\nColumns in Ref_Service_Types and all categories for low cardinality columns :\nService_Type_Code : 1, 2, 4, 3\nParent_Service_Type_Code : 1\nService_Type_Description : provide photo service, provide dinning service, provide adv promoting service, provide filming service\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE station_company (\n\t\"Station_ID\" INTEGER, \n\t\"Company_ID\" INTEGER, \n\t\"Rank_of_the_Year\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\", \"Company_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES gas_station (\"Station_ID\")\n)\n/\nColumns in station_company and all categories for low cardinality columns :\nStation_ID : 1, 11, 7, 4, 6, 10\nCompany_ID : 1, 6, 3, 10, 9\nRank_of_the_Year : 1, 13, 2, 4, 3, 9\n/\n \nCREATE TABLE \"Documents\" (\n\tdocument_code VARCHAR(15), \n\tdocument_structure_code VARCHAR(15) NOT NULL, \n\tdocument_type_code VARCHAR(15) NOT NULL, \n\taccess_count INTEGER, \n\tdocument_name VARCHAR(80), \n\tPRIMARY KEY (document_code), \n\tFOREIGN KEY(document_structure_code) REFERENCES \"Document_Structures\" (document_structure_code)\n)\n/\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_code : 510, 714, 217\naccess_count : 8208, 3289, 2294\ndocument_name : Learning English, Summer Sails, Learning Database\n/\n/\nColumns in Documents and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\ndocument_type_code : Book, Advertisement, CV, Paper\n/\n \nCREATE TABLE manufacturer (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Open_Year\" REAL, \n\t\"Name\" TEXT, \n\t\"Num_of_Factories\" INTEGER, \n\t\"Num_of_Shops\" INTEGER, \n\tPRIMARY KEY (\"Manufacturer_ID\")\n)\n/\nColumns in manufacturer and all categories for low cardinality columns :\nManufacturer_ID : 1, 2, 5, 7, 4, 6, 3\nOpen_Year : 2001.0, 2008.0, 2000.0, 1980.0, 1992.0, 1991.0, 1990.0\nName : Tomorrow, Chevrolet, Chevrolet House, Jiaju, Ford Make, IKEA, Dodge\nNum_of_Factories : 1, 38, 36, 21, 12, 3\nNum_of_Shops : 2, 7, 8, 24, 4, 19, 35\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n/\n \nCREATE TABLE \"Clients\" (\n\t\"Client_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER NOT NULL, \n\t\"Customer_Email_Address\" VARCHAR(255), \n\t\"Customer_Name\" VARCHAR(255), \n\t\"Customer_Phone\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Client_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tUNIQUE (\"Client_ID\")\n)\n/\nColumns in Clients and 3 examples in each column for high cardinality columns :\nClient_ID : 768, 887, 628\nAddress_ID : 201, 110, 180\nCustomer_Email_Address : strosin.keara@example.com, lacy92@example.com, westley30@example.net\nCustomer_Name : Krista, Marquis, Tevin\nCustomer_Phone : (745)818-8559x747, (042)912-3404x5135, (995)964-6385\n/\n/\nColumns in Clients and all categories for low cardinality columns :\nOther_Details : VIP, Super VIP, None\n/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\n/\n \nCREATE TABLE genres (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/\nColumns in genres and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Bossa Nova, Comedy, Opera\n/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE broadcast (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Time_of_day\" TEXT, \n\tPRIMARY KEY (\"Channel_ID\", \"Program_ID\"), \n\tFOREIGN KEY(\"Program_ID\") REFERENCES program (\"Program_ID\"), \n\tFOREIGN KEY(\"Channel_ID\") REFERENCES channel (\"Channel_ID\")\n)\n/\nColumns in broadcast and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nProgram_ID : 1, 2, 4, 3\nTime_of_day : Morning, Night, Noon\n/\n" }, { "role": "user", "content": "What is the zip code that has the lowest average mean sea level pressure?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_sea_level_pressure_inches.\nThe SQL query I'll be generating is:\nSELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Organization_Contact_Individuals\" (\n\tindividual_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tdate_contact_from DATETIME NOT NULL, \n\tdate_contact_to DATETIME, \n\tPRIMARY KEY (individual_id, organization_id), \n\tFOREIGN KEY(individual_id) REFERENCES \"Individuals\" (individual_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/\nColumns in Organization_Contact_Individuals and 3 examples in each column for high cardinality columns :\ndate_contact_from : 2016-07-26 09:08:15, 2016-04-21 03:55:35, 2017-01-06 09:38:54\ndate_contact_to : 2018-03-24 16:54:36, 2018-03-07 16:40:29, 2018-03-06 21:22:49\n/\n/\nColumns in Organization_Contact_Individuals and all categories for low cardinality columns :\nindividual_id : 13, 11, 5, 7, 8, 6, 14, 10, 9\norganization_id : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n/\n \nCREATE TABLE \"Lives_in\" (\n\tstuid INTEGER, \n\tdormid INTEGER, \n\troom_number INTEGER, \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid), \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Lives_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nroom_number : 153, 102, 301\n/\n/\nColumns in Lives_in and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"SAVINGS\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/\nColumns in SAVINGS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 4, 6, 3\nbalance : 80000.0, 230000.0, 999999999.0, 60.0, 240.0, 200000.0\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE player_coach (\n\t\"Player_ID\" INTEGER, \n\t\"Coach_ID\" INTEGER, \n\t\"Starting_year\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\", \"Coach_ID\"), \n\tFOREIGN KEY(\"Coach_ID\") REFERENCES coach (\"Coach_ID\"), \n\tFOREIGN KEY(\"Player_ID\") REFERENCES player (\"Player_ID\")\n)\n/\nColumns in player_coach and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 4, 6, 14, 3, 10\nCoach_ID : 1, 2, 5, 3\nStarting_year : 2012, 2010, 2011, 2013\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Student_Tests_Taken\" (\n\tregistration_id INTEGER NOT NULL, \n\tdate_test_taken DATETIME NOT NULL, \n\ttest_result VARCHAR(255), \n\tFOREIGN KEY(registration_id) REFERENCES \"Student_Course_Enrolment\" (registration_id)\n)\n/\nColumns in Student_Tests_Taken and 3 examples in each column for high cardinality columns :\ndate_test_taken : 2018-03-19 02:04:26, 2018-03-25 03:27:16, 2018-03-25 21:41:51\n/\n/\nColumns in Student_Tests_Taken and all categories for low cardinality columns :\nregistration_id : 16, 2, 5, 7, 17, 4, 12, 19, 10, 9\ntest_result : Fail, Pass\n/\n \nCREATE TABLE \"Ref_Service_Types\" (\n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\t\"Parent_Service_Type_Code\" CHAR(15), \n\t\"Service_Type_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Service_Type_Code\"), \n\tUNIQUE (\"Service_Type_Code\")\n)\n/\nColumns in Ref_Service_Types and all categories for low cardinality columns :\nService_Type_Code : 1, 2, 4, 3\nParent_Service_Type_Code : 1\nService_Type_Description : provide photo service, provide dinning service, provide adv promoting service, provide filming service\n/\n \nCREATE TABLE head (\n\t\"head_ID\" INTEGER, \n\tname TEXT, \n\tborn_state TEXT, \n\tage REAL, \n\tPRIMARY KEY (\"head_ID\")\n)\n/\nColumns in head and all categories for low cardinality columns :\nhead_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Jeff Maggert, Pádraig Harrington, Billy Mayfair, K. J. Choi, Dudley Hart, Sergio García, Stewart Cink, Tiger Woods, Nick Faldo, Franklin Langham\nborn_state : Delaware, Connecticut, Alabama, California, Florida\nage : 69.0, 67.0, 68.0, 53.0, 56.0, 52.0, 50.0, 43.0\n/\n \nCREATE TABLE \"Document_Locations\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Date_in_Location_From\" DATETIME NOT NULL, \n\t\"Date_in_Locaton_To\" DATETIME, \n\tPRIMARY KEY (\"Document_ID\", \"Location_Code\", \"Date_in_Location_From\"), \n\tFOREIGN KEY(\"Location_Code\") REFERENCES \"Ref_Locations\" (\"Location_Code\"), \n\tFOREIGN KEY(\"Date_in_Location_From\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Date_in_Locaton_To\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"All_Documents\" (\"Document_ID\")\n)\n/\nColumns in Document_Locations and all categories for low cardinality columns :\nDocument_ID : 230, 11, 252, 170, 7, 119, 260, 111, 166, 81\nLocation_Code : b, e, c, n, x\nDate_in_Location_From : 2009-08-18 03:29:08, 1972-03-31 09:47:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1985-05-13 12:19:43, 2008-06-08 12:45:38\nDate_in_Locaton_To : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1995-01-01 03:52:11, 2008-06-08 12:45:38\n/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n/\n \nCREATE TABLE \"Roles\" (\n\trole_code VARCHAR(15), \n\trole_description VARCHAR(80), \n\tPRIMARY KEY (role_code)\n)\n/\nColumns in Roles and all categories for low cardinality columns :\nrole_code : PROJ-MGR, DBA\nrole_description : Project Manager, Database Administrator\n/\n" }, { "role": "user", "content": "What is the average bike availability in stations that are not located in Palo Alto?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: status, station.\nFrom these tables, I'll be using the following columns: bikes_available, station_id, id, city, Palo Alto.\nThe SQL query I'll be generating is:\nSELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = \"Palo Alto\")" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_type_code VARCHAR(20) NOT NULL, \n\taddress_line_1 VARCHAR(80), \n\taddress_line_2 VARCHAR(80), \n\ttown_city VARCHAR(80), \n\tstate VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and all categories for low cardinality columns :\ncustomer_id : 120, 114, 113, 116, 117, 115, 119, 118\ncustomer_type_code : Defaults on payments, Good Credit Rating\naddress_line_1 : 92189 Gulgowski Ranch Apt. 683, 05355 Marcelle Radial, 039 Jedidiah Estate Suite 537, 72144 Katlynn Flat Suite 512, 518 Mann Park, 425 Roman Tunnel, 1566 Ramona Overpass Apt. 464, 144 Legros Landing\naddress_line_2 : Suite 151, Apt. 551, Suite 035, Suite 959, Apt. 245, Apt. 495, Apt. 828, Suite 054\ntown_city : Funkstad, Tyreekhaven, North Alisaville, Maryamport, Hansenbury, Port Joshuah, West Annamariestad, Sauerberg\nstate : Pennsylvania, Hawaii, Tennessee, Kansas, Colorado, Iowa, Florida\nemail_address : hsteuber@example.org, vbogisich@example.org, rzulauf@example.org, cayla.satterfield@example.net, paige.hyatt@example.com, lavonne.frami@example.com, ubeier@example.org, vida86@example.com\nphone_number : 548.373.3603x59134, 044-468-4549, 06963347450, 997.698.4779x882, +38(3)9011433816, 578.019.7943x328, 1-369-302-7623x576, 470-803-0244\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n/\n/\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : FM, PT, PP, CV, BK\nDocument_Type_Name : Book, Presentation, Paper, Film, CV\nDocument_Type_Description : fun, excellent, very good, good\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Apartment_Buildings\" (\n\tbuilding_id INTEGER NOT NULL, \n\tbuilding_short_name CHAR(15), \n\tbuilding_full_name VARCHAR(80), \n\tbuilding_description VARCHAR(255), \n\tbuilding_address VARCHAR(255), \n\tbuilding_manager VARCHAR(50), \n\tbuilding_phone VARCHAR(80), \n\tPRIMARY KEY (building_id), \n\tUNIQUE (building_id)\n)\n/\nColumns in Apartment_Buildings and 3 examples in each column for high cardinality columns :\nbuilding_id : 153, 734, 556\nbuilding_short_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_full_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_address : 012 Arnoldo Mountain\nGerholdland, ID 23342, 489 Josh Orchard Apt. 998\nSipesview, DE 69053, 601 Graham Roads\nPort Luz, VA 29660-6703\nbuilding_manager : Kyle, Emma, Kathlyn\nbuilding_phone : (948)040-1064x387, 1-724-982-9507x640, 544-148-5565x2847\n/\n/\nColumns in Apartment_Buildings and all categories for low cardinality columns :\nbuilding_description : Studio, Flat, Duplex\n/\n \nCREATE TABLE \"Regular_Orders\" (\n\tregular_order_id INTEGER, \n\tdistributer_id INTEGER NOT NULL, \n\tPRIMARY KEY (regular_order_id), \n\tFOREIGN KEY(distributer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Regular_Orders and 3 examples in each column for high cardinality columns :\nregular_order_id : 1, 13, 11\n/\n/\nColumns in Regular_Orders and all categories for low cardinality columns :\ndistributer_id : 1, 10, 2, 7, 8, 6, 12, 3, 14, 15\n/\n" }, { "role": "user", "content": "What is the average bike availablility for stations not in Palo Alto?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: status, station.\nFrom these tables, I'll be using the following columns: bikes_available, station_id, id, city, Palo Alto.\nThe SQL query I'll be generating is:\nSELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = \"Palo Alto\")" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n/\n\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n/\n \nCREATE TABLE temperature (\n\t\"City_ID\" INTEGER, \n\t\"Jan\" REAL, \n\t\"Feb\" REAL, \n\t\"Mar\" REAL, \n\t\"Apr\" REAL, \n\t\"Jun\" REAL, \n\t\"Jul\" REAL, \n\t\"Aug\" REAL, \n\t\"Sep\" REAL, \n\t\"Oct\" REAL, \n\t\"Nov\" REAL, \n\t\"Dec\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"City_ID\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in temperature and all categories for low cardinality columns :\nCity_ID : 1, 11, 2, 7, 4, 6, 3, 10\nJan : 18.9, 25.6, 18.3, 26.1, 17.8, 26.7, 17.2\nFeb : 18.9, 18.3, 26.1, 27.2, 17.8, 26.6, 17.2\nMar : 19.4, 18.3, 26.1, 26.6, 27.8\nApr : 18.9, 26.1, 20.6, 28.3, 27.8, 20.0\nJun : 22.8, 30.0, 30.6, 22.2, 20.6, 28.3, 27.8, 20.0\nJul : 31.1, 23.3, 28.9, 30.6, 20.6, 21.7, 27.8\nAug : 31.1, 31.7, 23.9, 23.3, 29.4, 20.6, 21.7, 28.3\nSep : 31.1, 21.1, 31.7, 23.3, 29.4, 20.6, 28.3\nOct : 22.8, 30.6, 28.9, 20.6, 28.3, 20.0\nNov : 19.4, 27.2, 28.9, 21.7, 20.0\nDec : 18.3, 26.1, 26.7, 27.8, 20.0\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n/\n \nCREATE TABLE event (\n\t\"Event_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\t\"Event_Attendance\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 4, 3\nDate : 9 April 2014, 7 October 2010, 11 October 2007, 13 October 2008, 20 June 2018\nVenue : Motagua, Platense, Hispano, Victoria, Marathon\nName : Global Awarding, Public Debating, Special Exhibition, Government Hearing, Olympia Games Openning\nEvent_Attendance : 369, 1675, 2356, 6650, 225\n/\n \nCREATE TABLE \"Features\" (\n\t\"Feature_ID\" INTEGER NOT NULL, \n\t\"Feature_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Feature_ID\")\n)\n/\nColumns in Features and all categories for low cardinality columns :\nFeature_ID : 955, 543, 681, 528, 523\nFeature_Details : park, shopping, cafe, parking, garden\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Graduation_College\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 4, 6, 3\nAge : 37, 25, 30, 34, 27, 31\nName : Tom Sheehey, Reggie Lewis, Brad Lohaus, David Butler, Tim Naegeli, Darryl Kennedy, Jerry Corcoran\nNationality : United States, United Kindom\nGraduation_College : Wisconsin–Stevens Point, California, Virginia, Iowa, Northeastern, Oklahoma\n/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n/\n \nCREATE TABLE building (\n\tbuilding_id TEXT, \n\t\"Name\" TEXT, \n\t\"Street_address\" TEXT, \n\t\"Years_as_tallest\" TEXT, \n\t\"Height_feet\" INTEGER, \n\t\"Floors\" INTEGER, \n\tPRIMARY KEY (building_id)\n)\n/\nColumns in building and all categories for low cardinality columns :\nbuilding_id : 1, 2, 5, 7, 4, 6, 3, 0\nName : Bank of America Tower, Franklin Exchange Building, One Tampa City Center, 100 North Tampa, Park Tower, Citizens Bank Building, Floridan Hotel, Tampa City Hall\nStreet_address : 905 Franklin Street, 701 North Franklin Street, 655 North Franklin Street, 315 John F. Kennedy Boulevard, 101 East Kennedy Boulevard, 100 North Tampa Street, 400 North Tampa Street, 201 North Franklin Street\nYears_as_tallest : 1966–1972, 1981–1986, 1913–1915, 1992–present, 1986–1992, 1915–1926, 1926–1966, 1972–1981\nHeight_feet : 204, 537, 458, 577, 145, 579, 160, 280\nFloors : 42, 36, 17, 12, 39, 10, 22\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Member_Name\" TEXT, \n\t\"Party_ID\" TEXT, \n\t\"In_office\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 13, 11\nMember_Name : Hon Bob Baldwin, Hon Kim Beazley, Kerry Bartlett\nIn_office : 1980–2007, 1996–2007, 1990–2010\n/\n/\nColumns in member and all categories for low cardinality columns :\nParty_ID : 1, 2, 3\n/\n" }, { "role": "user", "content": "What is the average longitude of stations that never had bike availability more than 10?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE endowment (\n\tendowment_id INTEGER, \n\t\"School_id\" INTEGER, \n\tdonator_name TEXT, \n\tamount REAL, \n\tPRIMARY KEY (endowment_id), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in endowment and 3 examples in each column for high cardinality columns :\nendowment_id : 1, 11, 2\ndonator_name : Santo Domingo Este, Duarte, San Cristóbal\namount : 9.05, 8.82, 8.85\n/\n/\nColumns in endowment and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n/\n/\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n/\n \nCREATE TABLE \"Plays_Games\" (\n\t\"StuID\" INTEGER, \n\t\"GameID\" INTEGER, \n\t\"Hours_Played\" INTEGER, \n\tFOREIGN KEY(\"GameID\") REFERENCES \"Video_Games\" (\"GameID\"), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Plays_Games and all categories for low cardinality columns :\nStuID : 1007, 1008, 1032, 1010, 1001\nGameID : 1, 2, 5, 4, 6, 3\nHours_Played : 1, 100, 10, 1000, 50, 47, 15, 1337, 35\n/\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n/\n/\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n/\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n/\n \nCREATE TABLE \"Apartments\" (\n\tapt_id INTEGER NOT NULL, \n\tbuilding_id INTEGER NOT NULL, \n\tapt_type_code CHAR(15), \n\tapt_number CHAR(10), \n\tbathroom_count INTEGER, \n\tbedroom_count INTEGER, \n\troom_count CHAR(5), \n\tPRIMARY KEY (apt_id), \n\tFOREIGN KEY(building_id) REFERENCES \"Apartment_Buildings\" (building_id), \n\tUNIQUE (apt_id)\n)\n/\nColumns in Apartments and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_number : Suite 307, Apt. 411, Apt. 585\n/\n/\nColumns in Apartments and all categories for low cardinality columns :\nbuilding_id : 153, 673, 808, 744, 624, 790, 191, 734, 225\napt_type_code : Studio, Flat, Duplex\nbathroom_count : 1, 2, 3\nbedroom_count : 5, 4, 6, 3\nroom_count : 5, 7, 8, 6, 3, 9\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n/\n \nCREATE TABLE \"Problem_Log\" (\n\tproblem_log_id INTEGER, \n\tassigned_to_staff_id INTEGER NOT NULL, \n\tproblem_id INTEGER NOT NULL, \n\tproblem_category_code VARCHAR(20) NOT NULL, \n\tproblem_status_code VARCHAR(20) NOT NULL, \n\tlog_entry_date DATETIME, \n\tlog_entry_description VARCHAR(255), \n\tlog_entry_fix VARCHAR(255), \n\tother_log_details VARCHAR(255), \n\tPRIMARY KEY (problem_log_id), \n\tFOREIGN KEY(problem_status_code) REFERENCES \"Problem_Status_Codes\" (problem_status_code), \n\tFOREIGN KEY(problem_id) REFERENCES \"Problems\" (problem_id), \n\tFOREIGN KEY(assigned_to_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(problem_category_code) REFERENCES \"Problem_Category_Codes\" (problem_category_code)\n)\n/\nColumns in Problem_Log and 3 examples in each column for high cardinality columns :\nproblem_log_id : 1, 13, 11\nlog_entry_date : 1997-08-31 08:19:12, 1974-09-13 00:37:26, 2011-11-12 23:30:53\nlog_entry_description : t, d, b\nlog_entry_fix : t, i, s\nother_log_details : d, f, b\n/\n/\nColumns in Problem_Log and all categories for low cardinality columns :\nassigned_to_staff_id : 1, 13, 11, 2, 5, 8, 4, 6, 12, 10\nproblem_id : 1, 13, 11, 10, 7, 8, 4, 12, 15\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_status_code : Solved, Reported\n/\n" }, { "role": "user", "content": "What is the mean longitude for all stations that have never had more than 10 bikes available?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE country (\n\t\"Country_id\" INTEGER, \n\t\"Country_name\" TEXT, \n\t\"Capital\" TEXT, \n\t\"Official_native_language\" TEXT, \n\tPRIMARY KEY (\"Country_id\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_id : 1, 2, 5, 4, 6, 3\nCountry_name : Isle of Man, Iran, United States, Indonesia, Iraq, Ireland\nCapital : Jakarta, Baghdad, Dublin, Tehran, Douglas, Washington\nOfficial_native_language : Arabic ( Arabic script ) Kurdish, English Manx, Persian ( Arabic script ), English, Bahasa Indonesia, Irish English\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n/\n \nCREATE TABLE jobs (\n\t\"JOB_ID\" VARCHAR(10) DEFAULT '' NOT NULL, \n\t\"JOB_TITLE\" VARCHAR(35) NOT NULL, \n\t\"MIN_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"MAX_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"JOB_ID\")\n)\n/\nColumns in jobs and 3 examples in each column for high cardinality columns :\nJOB_ID : HR_REP, ST_MAN, AD_PRES\nJOB_TITLE : Purchasing Clerk, Stock Clerk, Marketing Manager\nMIN_SALARY : 20000, 8000, 3000\nMAX_SALARY : 20000, 8500, 40000\n/\n\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n/\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tparent_product_id INTEGER, \n\tproduct_category_code VARCHAR(20) NOT NULL, \n\tdate_product_first_available DATETIME, \n\tdate_product_discontinued DATETIME, \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tproduct_price DECIMAL(19, 4), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\nparent_product_id : 8, 4, 9, 3\nproduct_category_code : Food, Book, Hardware\ndate_product_first_available : 1988-09-29 17:54:50, 1998-06-20 15:04:11, 1994-12-18 15:13:19, 1974-06-25 12:26:47\ndate_product_discontinued : 1987-12-20 13:46:16, 1997-07-02 18:26:16, 1980-06-26 10:40:19, 1991-08-20 05:22:31\nproduct_name : Chocolate, The Great Gatsby, Mouse, Keyboard\nproduct_description : Designed for games, Handmade chocolate, American novel, Blue tooth mouse\nproduct_price : 23.3500, 2.8800, 109.9900, 35.0000\n/\n \nCREATE TABLE festival_detail (\n\t\"Festival_ID\" INTEGER, \n\t\"Festival_Name\" TEXT, \n\t\"Chair_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Festival_ID\")\n)\n/\nColumns in festival_detail and all categories for low cardinality columns :\nFestival_ID : 1, 2, 5, 4, 3\nFestival_Name : Gobel Awards, LA Awards, Flower Awards, Panasonic Awards, Cherry Awards\nChair_Name : Doug Ford, Charles Coody, Lucy Lu, Arnold Palmer, Raymond Floyd\nLocation : United States\nYear : 2007, 2008, 2010, 2006\nNum_of_Audience : 160, 152, 161, 155\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n \nCREATE TABLE \"COURSE\" (\n\t\"CRS_CODE\" VARCHAR(10), \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"CRS_DESCRIPTION\" VARCHAR(35), \n\t\"CRS_CREDIT\" FLOAT, \n\tPRIMARY KEY (\"CRS_CODE\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/\nColumns in COURSE and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nDEPT_CODE : CIS, ACCT\nCRS_DESCRIPTION : Statistical Applications, Accounting I, Accounting II, Database Design and Implementation, Intro. to Microcomputing, Intro. to Statistics\nCRS_CREDIT : 3.0, 4.0\n/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n/\n" }, { "role": "user", "content": "When and in what zip code did max temperature reach 80?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, zip_code, max_temperature_f.\nThe SQL query I'll be generating is:\nSELECT date , zip_code FROM weather WHERE max_temperature_f >= 80" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE cinema (\n\t\"Cinema_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Openning_year\" INTEGER, \n\t\"Capacity\" INTEGER, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"Cinema_ID\")\n)\n/\nColumns in cinema and all categories for low cardinality columns :\nCinema_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Glenmore, Oriel, Codling, Dublin Array, Glenough, Grouse Lodge, Carrowleagh, Gortahile, Mount Callan, Moneypoint\nOpenning_year : 2009, 2013, 2015, 2012, 2011, 2010\nCapacity : 330, 305, 368, 364, 325, 203, 908, 208, 1100, 225\nLocation : County Cork, County Louth, County Laois, County Tipperary, County Clare, County Dublin, County Wicklow\n/\n \nCREATE TABLE \"Research_Staff\" (\n\tstaff_id INTEGER, \n\temployer_organisation_id INTEGER NOT NULL, \n\tstaff_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(employer_organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/\nColumns in Research_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_details : aspernatur, dicta, ab\n/\n/\nColumns in Research_Staff and all categories for low cardinality columns :\nemployer_organisation_id : 1, 2, 5, 8, 4, 6, 3, 10, 9\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Vehicles\" (\n\tvehicle_id INTEGER, \n\tvehicle_details VARCHAR(255), \n\tPRIMARY KEY (vehicle_id)\n)\n/\nColumns in Vehicles and all categories for low cardinality columns :\nvehicle_id : 1, 2, 3\nvehicle_details : Car, Van, Truck\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Ref_Payment_Methods\" (\n\tpayment_method_code CHAR(10) NOT NULL, \n\tpayment_method_description VARCHAR(80), \n\tPRIMARY KEY (payment_method_code), \n\tUNIQUE (payment_method_code)\n)\n/\nColumns in Ref_Payment_Methods and all categories for low cardinality columns :\npayment_method_code : Visa, MasterCard, American E\npayment_method_description : Visa, debit, credit\n/\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n/\n\n \nCREATE TABLE \"Minor_in\" (\n\t\"StuID\" INTEGER, \n\t\"DNO\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Minor_in and all categories for low cardinality columns :\nStuID : 1006, 1007, 1008, 1014, 1027, 1005, 1004, 1031, 1015, 1016\nDNO : 520, 90, 190, 140, 50, 540, 550, 530\n/\n \nCREATE TABLE \"Accounts\" (\n\t\"Account_ID\" INTEGER NOT NULL, \n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Account_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Account_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Statements\" (\"Statement_ID\")\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\nAccount_ID : 321, 427, 240\nAccount_Details : 12223.93, 6352.31, 930.14\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\nStatement_ID : 192, 57\n/\n \nCREATE TABLE \"Circulation_History\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tcopy_number INTEGER NOT NULL, \n\temployee_id INTEGER NOT NULL, \n\tPRIMARY KEY (document_id, draft_number, copy_number, employee_id), \n\tFOREIGN KEY(document_id, draft_number, copy_number) REFERENCES \"Draft_Copies\" (document_id, draft_number, copy_number), \n\tFOREIGN KEY(employee_id) REFERENCES \"Employees\" (employee_id)\n)\n/\nColumns in Circulation_History and all categories for low cardinality columns :\ndocument_id : 1, 10, 2, 20\ndraft_number : 1, 2, 17, 20\ncopy_number : 10, 15, 4, 5\nemployee_id : 1, 8, 2\n/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n/\n \nCREATE TABLE schedule (\n\t\"Cinema_ID\" INTEGER, \n\t\"Film_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Show_times_per_day\" INTEGER, \n\t\"Price\" FLOAT, \n\tPRIMARY KEY (\"Cinema_ID\", \"Film_ID\"), \n\tFOREIGN KEY(\"Cinema_ID\") REFERENCES cinema (\"Cinema_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\")\n)\n/\nColumns in schedule and all categories for low cardinality columns :\nCinema_ID : 1, 2, 6, 10, 9\nFilm_ID : 1, 2, 5, 4, 3\nDate : 20 May, 2 Aug, 11 July, 21 May, 19 May, 21 Jun\nShow_times_per_day : 2, 5, 4, 3\nPrice : 9.99, 8.99, 12.99, 15.99\n/\n \nCREATE TABLE teachers (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/\nColumns in teachers and 3 examples in each column for high cardinality columns :\nLastName : MOYER, NIBLER, ONDERSMA\nFirstName : CHARMAINE, JEROME, KIRK\nClassroom : 109, 108, 106\n/\n\n \nCREATE TABLE \"Apartment_Facilities\" (\n\tapt_id INTEGER NOT NULL, \n\tfacility_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (apt_id, facility_code), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id)\n)\n/\nColumns in Apartment_Facilities and all categories for low cardinality columns :\napt_id : 1, 2, 5, 6, 3, 15, 9\nfacility_code : Gym, Swimming Pool, Boardband, Cable TV\n/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"White\" REAL, \n\t\"Black\" REAL, \n\t\"Amerindian\" REAL, \n\t\"Asian\" REAL, \n\t\"Multiracial\" REAL, \n\t\"Hispanic\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"County_ID\") REFERENCES county_public_safety (\"County_ID\")\n)\n/\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 16, 13\nName : Aguadilla, Barranquitas, Bayamón\nWhite : 70.7, 78.3, 93.1\nBlack : 4.1, 22.8, 7.2\nMultiracial : 10.7, 12.1, 11.7\n/\n/\nColumns in city and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nAmerindian : 0.4, 0.6, 1.0, 0.3, 0.2, 0.9\nAsian : 0.1, 0.4, 0.3, 0.0, 0.2\nHispanic : 99.6, 98.5, 99.1, 99.5, 99.2, 99.4, 98.6, 98.9, 99.0, 99.3\n/\n" }, { "role": "user", "content": "What zip codes have a station with a max temperature greater than or equal to 80 and when did it reach that temperature?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, zip_code, max_temperature_f.\nThe SQL query I'll be generating is:\nSELECT date , zip_code FROM weather WHERE max_temperature_f >= 80" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Country\" (\n\tid INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Country and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\nname : Scotland, Italy, Spain\n/\n\n \nCREATE TABLE prereq (\n\tcourse_id VARCHAR(8), \n\tprereq_id VARCHAR(8), \n\tPRIMARY KEY (course_id, prereq_id), \n\tFOREIGN KEY(course_id) REFERENCES course (course_id), \n\tFOREIGN KEY(prereq_id) REFERENCES course (course_id)\n)\n/\nColumns in prereq and 3 examples in each column for high cardinality columns :\ncourse_id : 241, 586, 628\nprereq_id : 304, 628, 927\n/\n\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n/\n/\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Images\" (\n\timage_id INTEGER, \n\timage_alt_text VARCHAR(80), \n\timage_name VARCHAR(40), \n\timage_url VARCHAR(255), \n\tPRIMARY KEY (image_id)\n)\n/\nColumns in Images and 3 examples in each column for high cardinality columns :\nimage_id : 1, 13, 11\nimage_alt_text : Chaya, Ashtyn, Marianna\nimage_name : chapter3, data1, data2\nimage_url : http://www.bernierconnelly.com/1.jpg, http://www.hermann.com/1.jpg, http://connellykertzmann.org/1.jpg\n/\n\n \nCREATE TABLE medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\n/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(15) NOT NULL, \n\tshipping_method_code VARCHAR(15) NOT NULL, \n\torder_placed_datetime DATETIME NOT NULL, \n\torder_delivered_datetime DATETIME, \n\torder_shipping_charges VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_placed_datetime : 2009-01-18 20:06:19, 2008-10-23 06:42:10, 2009-07-05 20:02:55\norder_shipping_charges : 33.58, 77.32, 36.87\n/\n/\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 2, 5, 7, 8, 14, 12, 15, 9\norder_status_code : Paid, Delivered, Cancelled\nshipping_method_code : FedEx, UPS, Unspecified\norder_delivered_datetime : 2018-03-20 12:00:00\n/\n \nCREATE TABLE film_market_estimation (\n\t\"Estimation_ID\" INTEGER, \n\t\"Low_Estimate\" REAL, \n\t\"High_Estimate\" REAL, \n\t\"Film_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Market_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Estimation_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in film_market_estimation and all categories for low cardinality columns :\nEstimation_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nLow_Estimate : 80000.0, 39.0, 16.0, 3000.0, 300.0, 53.0, 960.0, 913.0, 8000.0\nHigh_Estimate : 39.0, 16.0, 1000.0, 53.0, 960.0, 913.0, 8000.0, 80400.0\nFilm_ID : 1, 2, 4, 3\nType : Mass human sacrifice, Mass suicide murder, Mass suicide\nMarket_ID : 1, 2, 3\nYear : 1978, 1945, 1973, 1994, 1995, 2000, 1997, 1487, 1944\n/\n \nCREATE TABLE \"Track\" (\n\t\"TrackId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(200) NOT NULL, \n\t\"AlbumId\" INTEGER DEFAULT NULL, \n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"GenreId\" INTEGER DEFAULT NULL, \n\t\"Composer\" VARCHAR(220) DEFAULT NULL, \n\t\"Milliseconds\" INTEGER NOT NULL, \n\t\"Bytes\" INTEGER DEFAULT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"TrackId\"), \n\tFOREIGN KEY(\"MediaTypeId\") REFERENCES \"MediaType\" (\"MediaTypeId\"), \n\tFOREIGN KEY(\"GenreId\") REFERENCES \"Genre\" (\"GenreId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Album\" (\"AlbumId\")\n)\n/\nColumns in Track and 3 examples in each column for high cardinality columns :\nTrackId : 87, 56, 65\nName : Snoopy's search-Red baron, The Winner Loses, Leave My Girl Alone\nAlbumId : 17, 9, 16\nComposer : Ned Fairchild, Tony Iommi, Bill Ward, Geezer Butler, Ozzy Osbourne, Berry Gordy, Jr./Janie Bradford\nMilliseconds : 263497, 307617, 204721\nBytes : 6859518, 2301989, 6420530\n/\n/\nColumns in Track and all categories for low cardinality columns :\nMediaTypeId : 1, 2\nGenreId : 1, 2, 5, 4, 6, 3\nUnitPrice : 0.99\n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Ref_Attraction_Types\" (\n\t\"Attraction_Type_Code\" CHAR(15) NOT NULL, \n\t\"Attraction_Type_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Attraction_Type_Code\"), \n\tUNIQUE (\"Attraction_Type_Code\")\n)\n/\nColumns in Ref_Attraction_Types and all categories for low cardinality columns :\nAttraction_Type_Code : 2, 5, 6, 3, 9\nAttraction_Type_Description : park, gallery, adventure, garden, museum\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n" }, { "role": "user", "content": "Give me ids for all the trip that took place in a zip code area with average mean temperature above 60." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, weather.\nFrom these tables, I'll be using the following columns: trip.id, trip.zip_code, weather.zip_code, weather.mean_temperature_f.\nThe SQL query I'll be generating is:\nSELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n/\n \nCREATE TABLE swimmer (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Nationality\" TEXT, \n\tmeter_100 REAL, \n\tmeter_200 TEXT, \n\tmeter_300 TEXT, \n\tmeter_400 TEXT, \n\tmeter_500 TEXT, \n\tmeter_600 TEXT, \n\tmeter_700 TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"ID\")\n)\n/\nColumns in swimmer and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3\nname : Przemysław Stańczyk, Grant Hackett, Federico Colbertaldo, Sébastien Rouault, Craig Stevens, Sergiy Fesenko, Oussama Mellouli, Ryan Cochrane\nNationality : Italy, Canada, Australia, Ukraine, France, Tunisia, Poland\nmeter_100 : 57.35, 57.31, 55.67, 57.84, 57.66, 57.34\nmeter_200 : 1:57.21, 1:54.40, 1:57.26, 1:57.10, 1:56.44, 1:56.34, 1:56.77\nmeter_300 : 2:56.64, 2:56.95, 2:57.10, 2:55.94, 2:53.46, 2:55.90, 2:56.02, 2:56.04\nmeter_400 : 3:55.72, 3:55.49, 3:55.36, 3:57.00, 3:52.93, 3:56.34, 3:57.12, 3:55.37\nmeter_500 : 4:54.48, 4:56.96, 4:55.08, 4:54.21, 4:54.19, 4:52.85, 4:57.03, 4:56.15\nmeter_600 : 5:54.45, 5:53.03, 5:52.92, 5:56.99, 5:56.31, 5:53.53, 5:57.10, 5:52.59\nmeter_700 : 6:55.07, 6:57.44, 6:50.91, 6:53.34, 6:52.58, 6:57.69, 6:50.80, 6:52.69\nTime : 7:55.39, 7:52.04, 7:47.91, 7:53.43, 7:46.95, 7:56.56, 7:48.67, 7:49.98\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_details VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_details : 92283 Lora Forges Suite 322, 41099 Crist Prairie Suite 507, 06959 Garett Meadows Apt. 259\ncity : Alvertatown, East Frederic, North Marquesfort\nzip_postcode : 838, 827, 674\nstate_province_county : Michigan, Tennessee, Kentucky\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Authorship\" (\n\t\"authID\" INTEGER, \n\t\"instID\" INTEGER, \n\t\"paperID\" INTEGER, \n\t\"authOrder\" INTEGER, \n\tPRIMARY KEY (\"authID\", \"instID\", \"paperID\"), \n\tFOREIGN KEY(\"authID\") REFERENCES \"Authors\" (\"authID\"), \n\tFOREIGN KEY(\"instID\") REFERENCES \"Inst\" (\"instID\"), \n\tFOREIGN KEY(\"paperID\") REFERENCES \"Papers\" (\"paperID\")\n)\n/\nColumns in Authorship and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\n/\n/\nColumns in Authorship and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\npaperID : 201, 204, 205, 200, 206, 203, 202\nauthOrder : 1, 2, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Order_Items\" (\n\t\"Order_Item_ID\" INTEGER NOT NULL, \n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Product_ID\" INTEGER NOT NULL, \n\t\"Order_Quantity\" VARCHAR(288), \n\t\"Other_Item_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Order_Item_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Customer_Orders\" (\"Order_ID\"), \n\tFOREIGN KEY(\"Product_ID\") REFERENCES \"Products\" (\"Product_ID\")\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\nOrder_Item_ID : 1, 13, 11\nOrder_ID : 1, 10, 11\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nProduct_ID : 300, 233, 46, 156, 83, 179, 216, 81, 273\nOrder_Quantity : 1, 2\nOther_Item_Details : None\n/\n \nCREATE TABLE happy_hour_member (\n\t\"HH_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Total_amount\" REAL, \n\tPRIMARY KEY (\"HH_ID\", \"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in happy_hour_member and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4\nMember_ID : 5, 9, 3\nTotal_amount : 4.9, 4.2, 20.9, 16.9, 16.92, 20.92\n/\n \nCREATE TABLE \"Theme_Parks\" (\n\t\"Theme_Park_ID\" INTEGER NOT NULL, \n\t\"Theme_Park_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Theme_Park_ID\"), \n\tFOREIGN KEY(\"Theme_Park_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Theme_Parks and all categories for low cardinality columns :\nTheme_Park_ID : 6523, 5265, 6476\nTheme_Park_Details : Sea World, Universal Studios, Disney\n/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n/\n \nCREATE TABLE \"Roles\" (\n\trole_code VARCHAR(15), \n\trole_description VARCHAR(80), \n\tPRIMARY KEY (role_code)\n)\n/\nColumns in Roles and all categories for low cardinality columns :\nrole_code : PROJ-MGR, DBA\nrole_description : Project Manager, Database Administrator\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "For each zip code, find the ids of all trips that have a higher average mean temperature above 60?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, weather.\nFrom these tables, I'll be using the following columns: trip.id, trip.zip_code, weather.zip_code, weather.mean_temperature_f.\nThe SQL query I'll be generating is:\nSELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcoupon_id INTEGER NOT NULL, \n\tgood_or_bad_customer VARCHAR(4), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tgender_mf VARCHAR(1), \n\tdate_became_customer DATETIME, \n\tdate_last_hire DATETIME, \n\tPRIMARY KEY (customer_id), \n\tFOREIGN KEY(coupon_id) REFERENCES \"Discount_Coupons\" (coupon_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\nfirst_name : Bridget, Marilou, Jailyn\nlast_name : Little, Greenholt, Schroeder\ndate_became_customer : 2017-02-28 14:40:25, 2015-05-05 20:29:01, 2015-07-21 09:24:57\ndate_last_hire : 2018-03-04 08:59:40, 2018-03-18 17:35:43, 2018-03-13 21:20:05\n/\n/\nColumns in Customers and all categories for low cardinality columns :\ncoupon_id : 1, 3, 11, 2, 7, 6, 14, 12, 10\ngood_or_bad_customer : bad, good\ngender_mf : 1, 0\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Studio\" TEXT, \n\t\"Director\" TEXT, \n\t\"Gross_in_dollar\" INTEGER, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and 3 examples in each column for high cardinality columns :\nFilm_ID : 1, 13, 11\nTitle : Annie, Rocky III, Tootsie\nDirector : Richard Attenborough, Nicholas Meyer, Ted Kotcheff\nGross_in_dollar : 53977250, 76606280, 125049125\n/\n/\nColumns in film and all categories for low cardinality columns :\nStudio : MGM, United Artists, Universal, 20th Century Fox, Columbia, Paramount, Columbia / Rastar, Paramount / Lorimar, Orion / Carolco, Universal / RKO\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE broadcast (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Time_of_day\" TEXT, \n\tPRIMARY KEY (\"Channel_ID\", \"Program_ID\"), \n\tFOREIGN KEY(\"Program_ID\") REFERENCES program (\"Program_ID\"), \n\tFOREIGN KEY(\"Channel_ID\") REFERENCES channel (\"Channel_ID\")\n)\n/\nColumns in broadcast and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nProgram_ID : 1, 2, 4, 3\nTime_of_day : Morning, Night, Noon\n/\n \nCREATE TABLE employee (\n\teid NUMERIC(9, 0), \n\tname TEXT(30), \n\tsalary NUMERIC(10, 2), \n\tPRIMARY KEY (eid)\n)\n/\nColumns in employee and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\nname : Dorthy Lewis, Jennifer Thomas, Eric Cooper\nsalary : 43001.00, 33546.00, 43723.00\n/\n\n \nCREATE TABLE \"Courses\" (\n\tcourse_id INTEGER, \n\tauthor_id INTEGER NOT NULL, \n\tsubject_id INTEGER NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tPRIMARY KEY (course_id), \n\tFOREIGN KEY(subject_id) REFERENCES \"Subjects\" (subject_id), \n\tFOREIGN KEY(author_id) REFERENCES \"Course_Authors_and_Tutors\" (author_id)\n)\n/\nColumns in Courses and 3 examples in each column for high cardinality columns :\ncourse_id : 1, 13, 11\ncourse_name : modern Arts, AI, Writing in French\ncourse_description : modern Arts, AI, Writing in French\n/\n/\nColumns in Courses and all categories for low cardinality columns :\nauthor_id : 13, 11, 5, 8, 4, 6, 14, 12, 15, 9\nsubject_id : 1, 2, 3\n/\n \nCREATE TABLE \"Images\" (\n\timage_id INTEGER, \n\timage_alt_text VARCHAR(80), \n\timage_name VARCHAR(40), \n\timage_url VARCHAR(255), \n\tPRIMARY KEY (image_id)\n)\n/\nColumns in Images and 3 examples in each column for high cardinality columns :\nimage_id : 1, 13, 11\nimage_alt_text : Chaya, Ashtyn, Marianna\nimage_name : chapter3, data1, data2\nimage_url : http://www.bernierconnelly.com/1.jpg, http://www.hermann.com/1.jpg, http://connellykertzmann.org/1.jpg\n/\n\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n/\n\n \nCREATE TABLE \"Product_Categories\" (\n\tproduction_type_code VARCHAR(15), \n\tproduct_type_description VARCHAR(80), \n\tvat_rating DECIMAL(19, 4), \n\tPRIMARY KEY (production_type_code)\n)\n/\nColumns in Product_Categories and all categories for low cardinality columns :\nproduction_type_code : Food, Books, DVDs, Electronics\nproduct_type_description : Food, Books, Dvd products, Electrical devices\nvat_rating : 15.8400, 11.4000, 13.9500, 17.9000\n/\n \nCREATE TABLE review (\n\ta_id INTEGER NOT NULL, \n\tu_id INTEGER NOT NULL, \n\ti_id INTEGER NOT NULL, \n\trating INTEGER DEFAULT NULL, \n\trank INTEGER DEFAULT NULL, \n\tPRIMARY KEY (a_id), \n\tFOREIGN KEY(i_id) REFERENCES item (i_id), \n\tFOREIGN KEY(u_id) REFERENCES useracct (u_id)\n)\n/\nColumns in review and all categories for low cardinality columns :\na_id : 1, 2, 5, 7, 4, 6, 3\nu_id : 1, 2\ni_id : 1, 5, 7, 4, 3\nrating : 7, 10, 5, 6\nrank : 1, 2, 5, 7, 4, 6, 3\n/\n \nCREATE TABLE mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\n \nCREATE TABLE playlist_tracks (\n\tplaylist_id INTEGER NOT NULL, \n\ttrack_id INTEGER NOT NULL, \n\tCONSTRAINT \"PK_PlaylistTrack\" PRIMARY KEY (playlist_id, track_id), \n\tFOREIGN KEY(playlist_id) REFERENCES playlists (id), \n\tFOREIGN KEY(track_id) REFERENCES tracks (id)\n)\n/\nColumns in playlist_tracks and 3 examples in each column for high cardinality columns :\ntrack_id : 1138, 537, 937\n/\n/\nColumns in playlist_tracks and all categories for low cardinality columns :\nplaylist_id : 1\n/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n/\n" }, { "role": "user", "content": "For each zip code, return how many times max wind speed reached 25?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, max_wind_Speed_mph.\nThe SQL query I'll be generating is:\nSELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Documents_with_Expenses\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Budget_Type_Code\") REFERENCES \"Ref_Budget_Codes\" (\"Budget_Type_Code\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Documents_with_Expenses and all categories for low cardinality columns :\nDocument_ID : 300, 240, 309, 226, 367, 371, 383, 227, 192, 57\nBudget_Type_Code : GV, SF, ORG\nDocument_Details : government, safety, organization\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n/\n/\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER NOT NULL, \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 79, 87, 16\ncustomer_details : Esteban Senger, Elva Boehm, Mr. Raul Prosacco\n/\n\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n \nCREATE TABLE \"Available_Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\tpolicy_type_code CHAR(15), \n\t\"Customer_Phone\" VARCHAR(255), \n\tPRIMARY KEY (\"Policy_ID\"), \n\tUNIQUE (\"Policy_ID\")\n)\n/\nColumns in Available_Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 751, 300, 586\nCustomer_Phone : (777)537-7792, 991.642.6485x822, 1-797-927-3585x9321\n/\n/\nColumns in Available_Policies and all categories for low cardinality columns :\npolicy_type_code : Property Insurance, Mortgage Insurance, Life Insurance, Travel Insurance\n/\n \nCREATE TABLE driver (\n\t\"Driver_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Home_city\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Driver_ID\")\n)\n/\nColumns in driver and 3 examples in each column for high cardinality columns :\nDriver_ID : 1, 11, 2\nName : Edwin Vargas, Henry Genga, Douglas McCrory\n/\n/\nColumns in driver and all categories for low cardinality columns :\nParty : Rep, Dem\nHome_city : Coventry, East Hartford, Hartford, Bethel, Manchester\nAge : 38, 45, 46, 37, 40, 36, 30, 52, 42, 35\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"pitStops\" (\n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\tstop INTEGER, \n\tlap INTEGER, \n\ttime TEXT, \n\tduration TEXT, \n\tmilliseconds INTEGER, \n\tPRIMARY KEY (\"raceId\", \"driverId\", stop), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/\nColumns in pitStops and all categories for low cardinality columns :\nraceId : \ndriverId : \nstop : \nlap : \ntime : \nduration : \nmilliseconds : \n/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n/\n/\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Invoices\" (\n\t\"Invoice_ID\" INTEGER NOT NULL, \n\t\"Order_ID\" INTEGER NOT NULL, \n\tpayment_method_code CHAR(15), \n\t\"Product_ID\" INTEGER NOT NULL, \n\t\"Order_Quantity\" VARCHAR(288), \n\t\"Other_Item_Details\" VARCHAR(255), \n\t\"Order_Item_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Invoice_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Customer_Orders\" (\"Order_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Bookings\" (\"Booking_ID\"), \n\tFOREIGN KEY(payment_method_code) REFERENCES \"Ref_Payment_Methods\" (payment_method_code)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\nInvoice_ID : 548, 398, 272\nOrder_ID : 1, 13, 11\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\npayment_method_code : Visa, MasterCard, American E\nProduct_ID : 2, 7, 8, 4, 6, 3, 9\nOrder_Quantity : 1, 2\nOther_Item_Details : None\nOrder_Item_ID : 1, 5, 7, 8, 4, 3, 9\n/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n/\n" }, { "role": "user", "content": "For each zip code, how many times has the maximum wind speed reached 25 mph?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, max_wind_Speed_mph.\nThe SQL query I'll be generating is:\nSELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Founded\" REAL, \n\t\"Denomination\" TEXT, \n\t\"Boys_or_Girls\" TEXT, \n\t\"Day_or_Boarding\" TEXT, \n\t\"Year_Entered_Competition\" REAL, \n\t\"School_Colors\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nSchool : St Aloysius' College, Cranbrook School, Waverley College, Knox Grammar School, Barker College, Trinity Grammar School\nLocation : Hornsby, Summer Hill, Waverley, Bellevue Hill, Milsons Point, Wahroonga\nEnrollment : 1000.0, 1850.0, 2200.0, 1200.0, 2300.0, 1430.0\nFounded : 1918.0, 1924.0, 1913.0, 1879.0, 1903.0, 1890.0\nDenomination : Catholic, Uniting Church, Anglican\nBoys_or_Girls : Boys only to Yr 9 Co-ed Year 10 to 12, Boys\nDay_or_Boarding : Day, Day & Boarding\nYear_Entered_Competition : 1944.0, 1929.0\nSchool_Colors : Royal Blue and Gold, Black & Blue, Red, White & Blue, Red & Blue, Green and White\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n/\n/\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE customers (\n\tid INTEGER, \n\tfirst_name VARCHAR(40) NOT NULL, \n\tlast_name VARCHAR(20) NOT NULL, \n\tcompany VARCHAR(80), \n\taddress VARCHAR(70), \n\tcity VARCHAR(40), \n\tstate VARCHAR(40), \n\tcountry VARCHAR(40), \n\tpostal_code VARCHAR(10), \n\tphone VARCHAR(24), \n\tfax VARCHAR(24), \n\temail VARCHAR(60) NOT NULL, \n\tsupport_rep_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(support_rep_id) REFERENCES employees (id)\n)\n/\nColumns in customers and 3 examples in each column for high cardinality columns :\nid : 53, 56, 49\nfirst_name : Astrid, Emma, Fynn\nlast_name : Sullivan, Schneider, Mercier\ncompany : Apple Inc., Microsoft Corporation, Rogers Canada\naddress : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\ncity : Oslo, Lisbon, Mountain View\nstate : AZ, NSW, Dublin\ncountry : Sweden, Australia, India\npostal_code : 85719, B3S 1C5, 1106\nphone : +1 (801) 531-7272, +49 030 26550280, +33 05 56 96 96 96\nfax : +1 (212) 221-4679, +55 (12) 3923-5566, +1 (650) 253-0000\nemail : mphilips12@shaw.ca, luisg@embraer.com.br, marc.dubois@hotmail.com\n/\n/\nColumns in customers and all categories for low cardinality columns :\nsupport_rep_id : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE school_details (\n\t\"School_ID\" INTEGER, \n\t\"Nickname\" TEXT, \n\t\"Colors\" TEXT, \n\t\"League\" TEXT, \n\t\"Class\" TEXT, \n\t\"Division\" TEXT, \n\tPRIMARY KEY (\"School_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_details and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nNickname : Auks, Raiders, Silver Eagles, Seahawks, Buccaneers, Tigers\nColors : Dark Green and White, Blue and Yellow, Maroon and White, Blue and Gold, Garnet and White, Silver and Maroon\nLeague : DSHA\nClass : Flight B, Flight A, Fight A\nDivision : Division 1, Division 2, Division 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Catalog_Contents_Additional_Attributes\" (\n\tcatalog_entry_id INTEGER NOT NULL, \n\tcatalog_level_number INTEGER NOT NULL, \n\tattribute_id INTEGER NOT NULL, \n\tattribute_value VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(catalog_level_number) REFERENCES \"Catalog_Structure\" (catalog_level_number), \n\tFOREIGN KEY(catalog_entry_id) REFERENCES \"Catalog_Contents\" (catalog_entry_id)\n)\n/\nColumns in Catalog_Contents_Additional_Attributes and all categories for low cardinality columns :\ncatalog_entry_id : 1, 11, 2, 5, 8, 4, 6, 12, 14, 15\ncatalog_level_number : 1, 8, 9\nattribute_id : 1, 2, 4, 3\nattribute_value : 1, 0\n/\n" }, { "role": "user", "content": "On which day and in which zip code was the min dew point lower than any day in zip code 94107?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, zip_code, min_dew_point_f.\nThe SQL query I'll be generating is:\nSELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n/\n/\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Event_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Service_ID\") REFERENCES \"Services\" (\"Service_ID\")\n)\n/\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n/\n/\nColumns in Events and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nEvent_Details : Fail, Success\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE machine (\n\t\"Machine_ID\" INTEGER, \n\t\"Making_Year\" INTEGER, \n\t\"Class\" TEXT, \n\t\"Team\" TEXT, \n\t\"Machine_series\" TEXT, \n\tvalue_points REAL, \n\tquality_rank INTEGER, \n\tPRIMARY KEY (\"Machine_ID\")\n)\n/\nColumns in machine and all categories for low cardinality columns :\nMachine_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMaking_Year : 1992, 1993, 1994, 1999, 1991, 1996, 1997, 1998, 1995\nClass : 125cc\nTeam : Honda, Team Givi- Honda LCR, Givi Racing- Honda, Marlboro Pileri - Honda, Hero Sports TS- Honda\nMachine_series : RS125\nvalue_points : 238.0, 105.0, 171.0, 129.0, 57.0, 62.0, 126.0, 194.0, 65.0\nquality_rank : 1, 13, 11, 2, 5, 7, 8, 4, 3\n/\n \nCREATE TABLE branch (\n\t\"Branch_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Open_year\" TEXT, \n\t\"Address_road\" TEXT, \n\t\"City\" TEXT, \n\tmembership_amount TEXT, \n\tPRIMARY KEY (\"Branch_ID\")\n)\n/\nColumns in branch and all categories for low cardinality columns :\nBranch_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Popert, Zytogorski, Alexandre, Brooke Greville, Taverner, Stanley, Saint Amant, Cochrane\nOpen_year : 2009, 2013, 2015, 2001, 2012, 2014\nAddress_road : Abbott Street, Concord Road, Brampton Road, Cecilia Avenue, Oaks Crescent, Valleys Place, Glebe Street, Abbey Rise\nCity : Oxford, London\nmembership_amount : 91, 56, 11, 1418, 7, 6, 112, 31\n/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE phone (\n\t\"Name\" TEXT, \n\t\"Phone_ID\" INTEGER, \n\t\"Memory_in_G\" INTEGER, \n\t\"Carrier\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Phone_ID\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nName : IPhone 6s, IPhone 7, IPhone X, IPhone 6, IPhone 5s\nPhone_ID : 1, 2, 5, 4, 3\nMemory_in_G : 128, 32, 16, 64\nCarrier : Sprint, TMobile\nPrice : 320.0, 1000.0, 480.0, 899.0, 699.0\n/\n \nCREATE TABLE film_market_estimation (\n\t\"Estimation_ID\" INTEGER, \n\t\"Low_Estimate\" REAL, \n\t\"High_Estimate\" REAL, \n\t\"Film_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Market_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Estimation_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in film_market_estimation and all categories for low cardinality columns :\nEstimation_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nLow_Estimate : 80000.0, 39.0, 16.0, 3000.0, 300.0, 53.0, 960.0, 913.0, 8000.0\nHigh_Estimate : 39.0, 16.0, 1000.0, 53.0, 960.0, 913.0, 8000.0, 80400.0\nFilm_ID : 1, 2, 4, 3\nType : Mass human sacrifice, Mass suicide murder, Mass suicide\nMarket_ID : 1, 2, 3\nYear : 1978, 1945, 1973, 1994, 1995, 2000, 1997, 1487, 1944\n/\n" }, { "role": "user", "content": "Which days had a minimum dew point smaller than any day in zip code 94107, and in which zip codes were those measurements taken?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, zip_code, min_dew_point_f.\nThe SQL query I'll be generating is:\nSELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE climber (\n\t\"Climber_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Time\" TEXT, \n\t\"Points\" REAL, \n\t\"Mountain_ID\" INTEGER, \n\tPRIMARY KEY (\"Climber_ID\"), \n\tFOREIGN KEY(\"Mountain_ID\") REFERENCES mountain (\"Mountain_ID\")\n)\n/\nColumns in climber and all categories for low cardinality columns :\nClimber_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Hans Luthringhauser, Charlie Freedman, Georg Auerbacher, Klaus Enders, Arseneus Butscher, Horst Owesle, Jean Claude Castella, Mick Horsepole, Siegfried Schauzu, L Currie\nCountry : West Germany, Switzerland, United Kingdom\nTime : 1:17.22.0, 1:25.02.8, 1:25.40.6, 1:27.28.8, 1:13.05.6, 1:18.14.6, 1:21.35.6, 1:17.16.0, 1:16.58.0, 1:14.56.4\nPoints : 8.0, 3.0, 12.0, 15.0, 10.0, 1.0, 6.0, 2.0, 4.0, 5.0\nMountain_ID : 1, 2, 5, 7, 3\n/\n \nCREATE TABLE swimmer (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Nationality\" TEXT, \n\tmeter_100 REAL, \n\tmeter_200 TEXT, \n\tmeter_300 TEXT, \n\tmeter_400 TEXT, \n\tmeter_500 TEXT, \n\tmeter_600 TEXT, \n\tmeter_700 TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"ID\")\n)\n/\nColumns in swimmer and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3\nname : Przemysław Stańczyk, Grant Hackett, Federico Colbertaldo, Sébastien Rouault, Craig Stevens, Sergiy Fesenko, Oussama Mellouli, Ryan Cochrane\nNationality : Italy, Canada, Australia, Ukraine, France, Tunisia, Poland\nmeter_100 : 57.35, 57.31, 55.67, 57.84, 57.66, 57.34\nmeter_200 : 1:57.21, 1:54.40, 1:57.26, 1:57.10, 1:56.44, 1:56.34, 1:56.77\nmeter_300 : 2:56.64, 2:56.95, 2:57.10, 2:55.94, 2:53.46, 2:55.90, 2:56.02, 2:56.04\nmeter_400 : 3:55.72, 3:55.49, 3:55.36, 3:57.00, 3:52.93, 3:56.34, 3:57.12, 3:55.37\nmeter_500 : 4:54.48, 4:56.96, 4:55.08, 4:54.21, 4:54.19, 4:52.85, 4:57.03, 4:56.15\nmeter_600 : 5:54.45, 5:53.03, 5:52.92, 5:56.99, 5:56.31, 5:53.53, 5:57.10, 5:52.59\nmeter_700 : 6:55.07, 6:57.44, 6:50.91, 6:53.34, 6:52.58, 6:57.69, 6:50.80, 6:52.69\nTime : 7:55.39, 7:52.04, 7:47.91, 7:53.43, 7:46.95, 7:56.56, 7:48.67, 7:49.98\n/\n \nCREATE TABLE tweets (\n\tid BIGINT NOT NULL, \n\tuid INTEGER NOT NULL, \n\ttext CHAR(140) NOT NULL, \n\tcreatedate DATETIME DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(uid) REFERENCES user_profiles (uid)\n)\n/\nColumns in tweets and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 9\nuid : 1, 5, 4, 6, 3\ntext : Today I have went shopping at Laffayette., Let’s celebrate women, fight for equality and support each other, not just today, but everyday!, Oh, I only have a few fans., I love my new boyfriend., I feel tired and don't want to write SQLs., My company is hiring interns., Hello I'm Tony Stark., I had a pretty rough time during the last couple of weeks\ncreatedate : 2018-03-09 20:00:14, 2018-03-12 02:30:30, 2018-03-09 20:01:02\n/\n \nCREATE TABLE section (\n\tcourse_id VARCHAR(8), \n\tsec_id VARCHAR(8), \n\tsemester VARCHAR(6), \n\tyear NUMERIC(4, 0), \n\tbuilding VARCHAR(15), \n\troom_number VARCHAR(7), \n\ttime_slot_id VARCHAR(4), \n\tPRIMARY KEY (course_id, sec_id, semester, year), \n\tFOREIGN KEY(course_id) REFERENCES course (course_id), \n\tFOREIGN KEY(building, room_number) REFERENCES classroom (building, room_number), \n\tCHECK (semester in ('Fall', 'Winter', 'Spring', 'Summer')), \n\tCHECK (year > 1701 and year < 2100)\n)\n/\nColumns in section and 3 examples in each column for high cardinality columns :\ncourse_id : 561, 304, 927\nbuilding : Nassau, Garfield, Saucon\nroom_number : 261, 375, 757\ntime_slot_id : E, N, K\n/\n/\nColumns in section and all categories for low cardinality columns :\nsec_id : 1, 2, 3\nsemester : Fall, Spring\nyear : 2004, 2009, 2001, 2005, 2008, 2006, 2002, 2003, 2010, 2007\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\n/\n \nCREATE TABLE driver (\n\t\"Driver_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Home_city\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Driver_ID\")\n)\n/\nColumns in driver and 3 examples in each column for high cardinality columns :\nDriver_ID : 1, 11, 2\nName : Edwin Vargas, Henry Genga, Douglas McCrory\n/\n/\nColumns in driver and all categories for low cardinality columns :\nParty : Rep, Dem\nHome_city : Coventry, East Hartford, Hartford, Bethel, Manchester\nAge : 38, 45, 46, 37, 40, 36, 30, 52, 42, 35\n/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n/\n" }, { "role": "user", "content": "For each trip, return its ending station's installation date." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.id, station.installation_date, trip.end_station_id, station.id.\nThe SQL query I'll be generating is:\nSELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Member_Name\" TEXT, \n\t\"Party_ID\" TEXT, \n\t\"In_office\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 13, 11\nMember_Name : Hon Bob Baldwin, Hon Kim Beazley, Kerry Bartlett\nIn_office : 1980–2007, 1996–2007, 1990–2010\n/\n/\nColumns in member and all categories for low cardinality columns :\nParty_ID : 1, 2, 3\n/\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n/\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Shop_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Open_Date\" TEXT, \n\t\"Open_Year\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/\nColumns in shop and 3 examples in each column for high cardinality columns :\nShop_ID : 1, 11, 2\nShop_Name : Pentre store, Best Buy, Apple\nOpen_Date : 24 February, 18 February, 1 January\n/\n/\nColumns in shop and all categories for low cardinality columns :\nLocation : Maerdy, Porth, Blaenllechau, Pentre, Penygraig, Gelli, Dinas, Wattstown, Cymmer\nOpen_Year : 2009, 2013, 2015, 2017, 2006, 2011, 2014, 2010, 2007\n/\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_address_id INTEGER NOT NULL, \n\tnickname VARCHAR(80), \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tdate_joined_staff DATETIME, \n\tdate_left_staff DATETIME, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(staff_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nnickname : ymiller, weissnat.vincenzo, nicholaus92\nfirst_name : Jedidiah, Eulalia, Camylle\nmiddle_name : Clarabelle, Maiya, Ulices\nlast_name : Sawayn, Maggio, Kuphal\ndate_of_birth : 2005-05-02 06:23:36, 2003-01-16 06:29:11, 2007-06-11 20:03:28\ndate_joined_staff : 2017-08-27 19:19:44, 2017-04-27 03:21:26, 2016-06-06 08:54:28\ndate_left_staff : 2018-03-08 12:31:16, 2018-03-10 15:25:00, 2018-03-24 10:11:08\n/\n/\nColumns in Staff and all categories for low cardinality columns :\nstaff_address_id : 1, 3, 13, 2, 5, 7, 4, 6, 12, 14\n/\n \nCREATE TABLE \"Companies\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value_billion\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Companies and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : PetroChina, Berkshire Hathaway, Petrobras\nSales_billion : 69.2, 189.6, 421.8\nProfits_billion : 16.4, 19.9, 17.4\nAssets_billion : 2467.9, 192.8, 1913.9\nMarket_Value_billion : 239.5, 186.5, 224.8\n/\n/\nColumns in Companies and all categories for low cardinality columns :\nHeadquarters : Spain, UK, China, Brazil, France, Russia, USA, Netherlands\nIndustry : Retailing, Conglomerate, Oil and gas, Telecommunications, Banking\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"View_Product_Availability\" (\n\tproduct_id INTEGER NOT NULL, \n\tbooking_id INTEGER NOT NULL, \n\tstatus_date DATETIME, \n\tavailable_yn VARCHAR(1), \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in View_Product_Availability and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 3\nbooking_id : 11, 5\nstatus_date : 2018-03-18 05:25:55, 2018-03-25 10:20:15, 2018-03-21 15:20:32, 2018-03-22 00:16:58\navailable_yn : 1, 0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n/\n/\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n/\n \nCREATE TABLE \"Bookings_Services\" (\n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Product_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Order_ID\", \"Product_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Bookings\" (\"Booking_ID\"), \n\tFOREIGN KEY(\"Product_ID\") REFERENCES \"Services\" (\"Service_ID\")\n)\n/\nColumns in Bookings_Services and all categories for low cardinality columns :\nOrder_ID : 1, 13, 5, 7, 8, 4, 12, 14, 9\nProduct_ID : 640, 630, 779, 525, 396, 773, 414, 597, 191\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n*/\n" }, { "role": "user", "content": "What is the installation date for each ending station on all the trips?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.id, station.installation_date, trip.end_station_id, station.id.\nThe SQL query I'll be generating is:\nSELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE locations (\n\t\"LOCATION_ID\" DECIMAL(4, 0) DEFAULT '0' NOT NULL, \n\t\"STREET_ADDRESS\" VARCHAR(40) DEFAULT NULL, \n\t\"POSTAL_CODE\" VARCHAR(12) DEFAULT NULL, \n\t\"CITY\" VARCHAR(30) NOT NULL, \n\t\"STATE_PROVINCE\" VARCHAR(25) DEFAULT NULL, \n\t\"COUNTRY_ID\" VARCHAR(2) DEFAULT NULL, \n\tPRIMARY KEY (\"LOCATION_ID\"), \n\tFOREIGN KEY(\"COUNTRY_ID\") REFERENCES countries (\"COUNTRY_ID\")\n)\n/\nColumns in locations and 3 examples in each column for high cardinality columns :\nLOCATION_ID : 1900, 1700, 1200\nSTREET_ADDRESS : 2004 Charade Rd, Mariano Escobedo 9991, 9450 Kamiya-cho\nPOSTAL_CODE : , 1689, 98199\nCITY : Tokyo, Southlake, South San Francisco\nSTATE_PROVINCE : , New South Wales, Sao Paulo\nCOUNTRY_ID : AU, NL, JP\n/\n\n \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n/\n \nCREATE TABLE wine (\n\t\"No\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Winery\" TEXT, \n\t\"Appelation\" TEXT, \n\t\"State\" TEXT, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Price\" INTEGER, \n\t\"Score\" INTEGER, \n\t\"Cases\" INTEGER, \n\t\"Drink\" TEXT, \n\tFOREIGN KEY(\"Grape\") REFERENCES grapes (\"Grape\"), \n\tFOREIGN KEY(\"Appelation\") REFERENCES appellations (\"Appelation\")\n)\n/\nColumns in wine and 3 examples in each column for high cardinality columns :\nNo : 87, 56, 65\nWinery : Novy, Turnbull, Loring\nAppelation : Mendocino County, Happy Canyon of Santa Barbara, Russian River Valley\nName : Wheelhouse, Limited Release, Mother Clone\nPrice : 56, 65, 75\nScore : 87, 91, 89\nCases : NULL, 377, 575\n/\n/\nColumns in wine and all categories for low cardinality columns :\nGrape : Sauvignon Blanc, Pinot Noir, Malbec, Merlot, Petite Sirah, Syrah, Cabernet Sauvingnon, Grenache, Zinfandel\nState : California\nYear : 2006, 2008, 2009, 2007\nDrink : 2013, 2001, 2012, 2011, now, 2010\n/\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n/\n/\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n/\n \nCREATE TABLE \"Benefits_Overpayments\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Benefits_Overpayments and all categories for low cardinality columns :\ncouncil_tax_id : 7, 8, 6, 3\ncmi_cross_ref_id : 83, 65, 41, 48\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE useracct (\n\tu_id INTEGER NOT NULL, \n\tname VARCHAR(128) DEFAULT NULL, \n\tPRIMARY KEY (u_id)\n)\n/\nColumns in useracct and all categories for low cardinality columns :\nu_id : 1, 2, 5, 7, 4, 6, 3\nname : Rosie, Emily, Roxi, Helen, Terry, Mark, Nancy\n/\n \nCREATE TABLE \"Projects\" (\n\t\"Project_ID\" INTEGER NOT NULL, \n\t\"Project_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Project_ID\")\n)\n/\nColumns in Projects and all categories for low cardinality columns :\nProject_ID : 35, 30, 134, 105, 195\nProject_Details : Graph Database project, Internet of Things project, Population Research project, Society Research project, Human Resource project\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Performers\" (\n\t\"Performer_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER NOT NULL, \n\t\"Customer_Name\" VARCHAR(255), \n\t\"Customer_Phone\" VARCHAR(255), \n\t\"Customer_Email_Address\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Performer_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tUNIQUE (\"Performer_ID\")\n)\n/\nColumns in Performers and 3 examples in each column for high cardinality columns :\nPerformer_ID : 153, 415, 650\nAddress_ID : 110, 124, 207\nCustomer_Name : Fritz, Jeanie, Oren\nCustomer_Phone : 1-952-052-6685x28082, 858.603.7004, 547.535.3455\nCustomer_Email_Address : anderson34@example.net, krogahn@example.com, ianderson@example.com\n/\n/\nColumns in Performers and all categories for low cardinality columns :\nOther_Details : Pay good tips, Did not pay, None\n/\n \nCREATE TABLE \"Party_Addresses\" (\n\tparty_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_address_from DATETIME NOT NULL, \n\taddress_type_code VARCHAR(15) NOT NULL, \n\tdate_address_to DATETIME, \n\tPRIMARY KEY (party_id, address_id), \n\tFOREIGN KEY(party_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Party_Addresses and 3 examples in each column for high cardinality columns :\ndate_address_from : 2016-11-02 02:06:07, 2016-04-15 03:54:06, 2016-06-09 00:48:07\ndate_address_to : 2018-02-09 08:47:26, 2018-02-27 09:21:41, 2018-03-07 13:28:44\n/\n/\nColumns in Party_Addresses and all categories for low cardinality columns :\nparty_id : 11, 5, 15, 8, 4, 6, 3, 10\naddress_id : 1, 13, 2, 5, 7, 8, 4, 10, 9\naddress_type_code : Billing, Residence, Delivery\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Team\" (\n\tid INTEGER, \n\tteam_api_id INTEGER, \n\tteam_fifa_api_id INTEGER, \n\tteam_long_name TEXT, \n\tteam_short_name TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Team and 3 examples in each column for high cardinality columns :\nid : 9553, 14876, 9547\nteam_api_id : 9761, 9875, 9847\nteam_fifa_api_id : 65, 1907, 1926\nteam_long_name : Lecce, AS Saint-Étienne, Stade Rennais FC\nteam_short_name : SIE, NIC, BAS\n/\n\n" }, { "role": "user", "content": "Which trip started from the station with the largest dock count? Give me the trip id." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.id, trip.start_station_id, station.id, station.dock_count.\nThe SQL query I'll be generating is:\nSELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n/\n/\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n/\n \nCREATE TABLE pilot_record (\n\t\"Record_ID\" INTEGER, \n\t\"Pilot_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\t\"Date\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\", \"Aircraft_ID\", \"Date\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Pilot_ID\") REFERENCES pilot (\"Pilot_ID\")\n)\n/\nColumns in pilot_record and all categories for low cardinality columns :\nRecord_ID : 1, 2, 5, 4, 6, 3\nPilot_ID : 1, 2, 4, 3\nAircraft_ID : 1, 2, 5, 4, 6\nDate : 2006/01/04, 2005/01/04, 2008/01/04, 2004/01/04, 2007/01/04, 2003/01/04\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"CMI_Cross_References\" (\n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tmaster_customer_id INTEGER NOT NULL, \n\tsource_system_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (cmi_cross_ref_id), \n\tFOREIGN KEY(master_customer_id) REFERENCES \"Customer_Master_Index\" (master_customer_id)\n)\n/\nColumns in CMI_Cross_References and 3 examples in each column for high cardinality columns :\ncmi_cross_ref_id : 65, 75, 102\n/\n/\nColumns in CMI_Cross_References and all categories for low cardinality columns :\nmaster_customer_id : 1, 2, 5, 4, 3, 9\nsource_system_code : Rent, Electoral, Business, Parking, Tax, Benefits\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Graduation_College\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 4, 6, 3\nAge : 37, 25, 30, 34, 27, 31\nName : Tom Sheehey, Reggie Lewis, Brad Lohaus, David Butler, Tim Naegeli, Darryl Kennedy, Jerry Corcoran\nNationality : United States, United Kindom\nGraduation_College : Wisconsin–Stevens Point, California, Virginia, Iowa, Northeastern, Oklahoma\n/\n \nCREATE TABLE \"Lots\" (\n\tlot_id INTEGER, \n\tinvestor_id INTEGER NOT NULL, \n\tlot_details VARCHAR(255), \n\tPRIMARY KEY (lot_id), \n\tFOREIGN KEY(investor_id) REFERENCES \"Investors\" (investor_id)\n)\n/\nColumns in Lots and 3 examples in each column for high cardinality columns :\nlot_id : 1, 13, 11\n/\n/\nColumns in Lots and all categories for low cardinality columns :\ninvestor_id : 1, 16, 13, 20, 7, 6, 19, 10, 9\nlot_details : d, m, q, s, r, h, x, z\n/\n \nCREATE TABLE protein (\n\tcommon_name TEXT, \n\tprotein_name TEXT, \n\tdivergence_from_human_lineage REAL, \n\taccession_number TEXT, \n\tsequence_length REAL, \n\tsequence_identity_to_human_protein TEXT, \n\t\"Institution_id\" TEXT, \n\tPRIMARY KEY (common_name), \n\tFOREIGN KEY(\"Institution_id\") REFERENCES \"Institution\" (\"Institution_id\")\n)\n/\nColumns in protein and all categories for low cardinality columns :\ncommon_name : Tropical Clawed Frog, porkworm, body louse, southern house mosquito, purple sea urchin\nprotein_name : uncharacterized protein LOC578090, conserved hypothetical protein, Centromeric protein E, putative, surface antigen repeat family protein, uncharacterized protein C20orf117-like\ndivergence_from_human_lineage : 937.5, 742.9, 782.7, 371.2\naccession_number : XP_003380263.1, XP_002942331.1, XP_783370.2, XP_002429877.1, XP_001843754.1\nsequence_length : 2030.0, 1587.0, 2086.0, 1584.0, 1878.0\nsequence_identity_to_human_protein : 30%, 47%, 36%, 39%, 32%\nInstitution_id : 1, 5, 9, 3\n/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n/\n \nCREATE TABLE \"Apartments\" (\n\tapt_id INTEGER NOT NULL, \n\tbuilding_id INTEGER NOT NULL, \n\tapt_type_code CHAR(15), \n\tapt_number CHAR(10), \n\tbathroom_count INTEGER, \n\tbedroom_count INTEGER, \n\troom_count CHAR(5), \n\tPRIMARY KEY (apt_id), \n\tFOREIGN KEY(building_id) REFERENCES \"Apartment_Buildings\" (building_id), \n\tUNIQUE (apt_id)\n)\n/\nColumns in Apartments and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_number : Suite 307, Apt. 411, Apt. 585\n/\n/\nColumns in Apartments and all categories for low cardinality columns :\nbuilding_id : 153, 673, 808, 744, 624, 790, 191, 734, 225\napt_type_code : Studio, Flat, Duplex\nbathroom_count : 1, 2, 3\nbedroom_count : 5, 4, 6, 3\nroom_count : 5, 7, 8, 6, 3, 9\n/\n \nCREATE TABLE teaches (\n\t\"ID\" VARCHAR(5), \n\tcourse_id VARCHAR(8), \n\tsec_id VARCHAR(8), \n\tsemester VARCHAR(6), \n\tyear NUMERIC(4, 0), \n\tPRIMARY KEY (\"ID\", course_id, sec_id, semester, year), \n\tFOREIGN KEY(course_id, sec_id, semester, year) REFERENCES section (course_id, sec_id, semester, year), \n\tFOREIGN KEY(\"ID\") REFERENCES instructor (\"ID\")\n)\n/\nColumns in teaches and 3 examples in each column for high cardinality columns :\nID : 99052, 6569, 79081\ncourse_id : 561, 304, 927\n/\n/\nColumns in teaches and all categories for low cardinality columns :\nsec_id : 1, 2, 3\nsemester : Fall, Spring\nyear : 2004, 2009, 2001, 2005, 2008, 2006, 2003, 2002, 2010, 2007\n/\n \nCREATE TABLE \"Projects\" (\n\t\"Code\" CHAR(4), \n\t\"Name\" CHAR(50) NOT NULL, \n\t\"Hours\" INTEGER, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Projects and 3 examples in each column for high cardinality columns :\nCode : Bte2, AeH6, Ast3\nName : Aerodynamics of Air Hockey, Winds: Studying Bernoullis Principle, Aerodynamics and Gas Mileage\nHours : 321, 189, 89\n/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n*/\n" }, { "role": "user", "content": "What is the id of the trip that started from the station with the highest dock count?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.id, trip.start_station_id, station.id, station.dock_count.\nThe SQL query I'll be generating is:\nSELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE region (\n\t\"Region_ID\" INTEGER, \n\t\"Region_name\" TEXT, \n\t\"Date\" TEXT, \n\t\"Label\" TEXT, \n\t\"Format\" TEXT, \n\t\"Catalogue\" TEXT, \n\tPRIMARY KEY (\"Region_ID\")\n)\n/\nColumns in region and all categories for low cardinality columns :\nRegion_ID : 1, 2, 5, 4, 3\nRegion_name : Japan, United Kingdom, United States\nDate : 1 July 2002, 16 July 2002, 3 July 2002\nLabel : Toshiba-EMI, Astralwerks, Parlophone\nFormat : CD digipak, 2× LP, CD\nCatalogue : ASW 40362, ASW 40522, 539 9821, TOCP-66045, 540 3622\n/\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER, \n\t\"Channel_ID\" INTEGER NOT NULL, \n\t\"Event_Type_Code\" CHAR(15), \n\t\"Finance_ID\" INTEGER NOT NULL, \n\t\"Location_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Location_ID\") REFERENCES \"Locations\" (\"Location_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tFOREIGN KEY(\"Finance_ID\") REFERENCES \"Finances\" (\"Finance_ID\"), \n\tUNIQUE (\"Event_ID\")\n)\n/\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 11\nChannel_ID : 1, 13, 11\nFinance_ID : 1, 13, 10\n/\n/\nColumns in Events and all categories for low cardinality columns :\nAddress_ID : 13, 10, 2, 12, 3, 14, 15, 9\nEvent_Type_Code : Press Conferenc, Seminar, Ceremonies, Conference, Trade Show\nLocation_ID : 13, 11, 10, 5, 7, 8, 6, 12, 15, 9\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE \"Lives_in\" (\n\tstuid INTEGER, \n\tdormid INTEGER, \n\troom_number INTEGER, \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid), \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Lives_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nroom_number : 153, 102, 301\n/\n/\nColumns in Lives_in and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n/\n \nCREATE TABLE mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Engineer_Skills\" (\n\tengineer_id INTEGER NOT NULL, \n\tskill_id INTEGER NOT NULL, \n\tFOREIGN KEY(skill_id) REFERENCES \"Skills\" (skill_id), \n\tFOREIGN KEY(engineer_id) REFERENCES \"Maintenance_Engineers\" (engineer_id)\n)\n/\nColumns in Engineer_Skills and 3 examples in each column for high cardinality columns :\nengineer_id : 13, 11, 2\n/\n/\nColumns in Engineer_Skills and all categories for low cardinality columns :\nskill_id : 1, 2, 3\n/\n \nCREATE TABLE member_attendance (\n\t\"Member_ID\" INTEGER, \n\t\"Performance_ID\" INTEGER, \n\t\"Num_of_Pieces\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Performance_ID\"), \n\tFOREIGN KEY(\"Performance_ID\") REFERENCES performance (\"Performance_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in member_attendance and all categories for low cardinality columns :\nMember_ID : 1, 11, 2, 5, 7, 4, 3\nPerformance_ID : 1, 2, 4, 6, 3\nNum_of_Pieces : 1, 2, 4, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Apartment_Buildings\" (\n\tbuilding_id INTEGER NOT NULL, \n\tbuilding_short_name CHAR(15), \n\tbuilding_full_name VARCHAR(80), \n\tbuilding_description VARCHAR(255), \n\tbuilding_address VARCHAR(255), \n\tbuilding_manager VARCHAR(50), \n\tbuilding_phone VARCHAR(80), \n\tPRIMARY KEY (building_id), \n\tUNIQUE (building_id)\n)\n/\nColumns in Apartment_Buildings and 3 examples in each column for high cardinality columns :\nbuilding_id : 153, 734, 556\nbuilding_short_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_full_name : VIA 57 WEST, Petersfield, The Clinton\nbuilding_address : 012 Arnoldo Mountain\nGerholdland, ID 23342, 489 Josh Orchard Apt. 998\nSipesview, DE 69053, 601 Graham Roads\nPort Luz, VA 29660-6703\nbuilding_manager : Kyle, Emma, Kathlyn\nbuilding_phone : (948)040-1064x387, 1-724-982-9507x640, 544-148-5565x2847\n/\n/\nColumns in Apartment_Buildings and all categories for low cardinality columns :\nbuilding_description : Studio, Flat, Duplex\n/\n" }, { "role": "user", "content": "Count the number of trips that did not end in San Francisco city." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.end_station_id, station.id, station.city, San Francisco.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != \"San Francisco\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 9\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE coach (\n\t\"Coach_ID\" INTEGER, \n\t\"Coach_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Coach_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in coach and all categories for low cardinality columns :\nCoach_ID : 1, 2, 5, 4, 3\nCoach_name : Robert Chen, James Wong, Smith Brown, Jameson Tomas, Joe Fabbri\nGender : F, M\nClub_ID : 1, 3\nRank : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"Roles\" (\n\t\"Role_Code\" CHAR(15) NOT NULL, \n\t\"Role_Name\" VARCHAR(255), \n\t\"Role_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Role_Code\")\n)\n/\nColumns in Roles and all categories for low cardinality columns :\nRole_Code : PR, HR, PT, MG, ED\nRole_Name : Proof Reader, Human Resource, Editor, Photo, Manager\nRole_Description : Itaque dolor ut nemo rerum vitae provident. Vel laborum ipsum velit sint. Et est omnis dignissimos., Ut sed quae eaque mollitia qui hic. Natus ea expedita et odio illum fugiat qui natus. Consequatur velit ut dolorem cum ullam esse deserunt dignissimos. Enim non non rem officiis quis., Aut modi nihil molestias temporibus sit rerum. Sit neque eaque odio omnis incidunt., Vero harum corrupti odit ipsa vero et odio. Iste et recusandae temporibus maxime. Magni aspernatur fugit quis explicabo totam esse corrupti., Et totam est quibusdam aspernatur ut. Vitae perferendis eligendi voluptatem molestiae rem ut enim. Ipsum expedita quae earum unde est. Repellendus ut ipsam nihil accusantium sit. Magni accusantium numquam quod et.\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n/\n/\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n/\n/\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(10) NOT NULL, \n\tproduct_name VARCHAR(80), \n\tproduct_price DECIMAL(19, 4), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : black topping, yellow jeans, red jeans\nproduct_price : 534.5200, 939.5700, 916.5300\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Clothes, Hardware\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE film_category (\n\tfilm_id INTEGER NOT NULL, \n\tcategory_id INTEGER NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (film_id, category_id), \n\tFOREIGN KEY(film_id) REFERENCES film (film_id), \n\tFOREIGN KEY(category_id) REFERENCES category (category_id)\n)\n/\nColumns in film_category and 3 examples in each column for high cardinality columns :\nfilm_id : 87, 56, 65\ncategory_id : 1, 16, 3\n/\n/\nColumns in film_category and all categories for low cardinality columns :\nlast_update : 2006-02-15 05:07:09\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_first_name VARCHAR(80), \n\tstaff_last_name VARCHAR(80), \n\tother_staff_details VARCHAR(255), \n\tPRIMARY KEY (staff_id)\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_first_name : Junius, Israel, Kenyatta\nstaff_last_name : Mante, Treutel, Weber\n/\n/\nColumns in Staff and all categories for low cardinality columns :\nother_staff_details : d, m, q, b, i, e, w, j, p, x\n/\n \nCREATE TABLE \"Reviewer\" (\n\t\"rID\" INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (\"rID\")\n)\n/\nColumns in Reviewer and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nname : Chris Jackson, Sarah Martinez, Mike Anderson, James Cameron, Elizabeth Thomas, Brittany Harris, Daniel Lewis, Ashley White\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "How many trips did not end in San Francisco?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip, station.\nFrom these tables, I'll be using the following columns: trip.end_station_id, station.id, station.city, San Francisco.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != \"San Francisco\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"White\" REAL, \n\t\"Black\" REAL, \n\t\"Amerindian\" REAL, \n\t\"Asian\" REAL, \n\t\"Multiracial\" REAL, \n\t\"Hispanic\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"County_ID\") REFERENCES county_public_safety (\"County_ID\")\n)\n/\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 16, 13\nName : Aguadilla, Barranquitas, Bayamón\nWhite : 70.7, 78.3, 93.1\nBlack : 4.1, 22.8, 7.2\nMultiracial : 10.7, 12.1, 11.7\n/\n/\nColumns in city and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nAmerindian : 0.4, 0.6, 1.0, 0.3, 0.2, 0.9\nAsian : 0.1, 0.4, 0.3, 0.0, 0.2\nHispanic : 99.6, 98.5, 99.1, 99.5, 99.2, 99.4, 98.6, 98.9, 99.0, 99.3\n/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE airports (\n\tapid INTEGER, \n\tname TEXT NOT NULL, \n\tcity TEXT, \n\tcountry TEXT, \n\tx REAL, \n\ty REAL, \n\televation BIGINT, \n\tiata TEXT(3), \n\ticao TEXT(4), \n\tPRIMARY KEY (apid)\n)\n/\nColumns in airports and 3 examples in each column for high cardinality columns :\napid : 87, 56, 65\nname : Rouyn Noranda Airport, Edmonton International Airport, Val-d'Or Airport\ncity : Medicine Hat, Sarnia, Fort Saint John\nx : -117.4469985961914, -122.054000854, -135.067001343\ny : 45.5175018311, 50.29029846191406, 47.697400654599996\nelevation : 87, 586, 56\niata : NULL, YYE, YXJ\nicao : CYXD, CYBK, CYMO\n/\n/\nColumns in airports and all categories for low cardinality columns :\ncountry : Iceland, Papua New Guinea, Greenland, Canada\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_Type_Code\" CHAR(15) NOT NULL, \n\t\"Start_Date\" DATETIME, \n\t\"End_Date\" DATETIME, \n\tPRIMARY KEY (\"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\")\n)\n/\nColumns in Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 703, 151, 768\nStart_Date : 2018-03-13 12:30:19, 2018-02-10 08:56:30, 2018-07-21 10:36:53\nEnd_Date : 2017-10-07 08:29:25, 2018-01-19 22:45:33, 2018-03-07 13:52:47\n/\n/\nColumns in Policies and all categories for low cardinality columns :\nCustomer_ID : 588, 858, 808, 334, 252, 994, 380, 430, 857, 435\nPolicy_Type_Code : Uniformed, Normal, Jurisdiction, Deputy\n/\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n/\n \nCREATE TABLE \"Lessons\" (\n\tlesson_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tlesson_status_code VARCHAR(15) NOT NULL, \n\tstaff_id INTEGER, \n\tvehicle_id INTEGER NOT NULL, \n\tlesson_date DATETIME, \n\tlesson_time VARCHAR(10), \n\tprice DOUBLE, \n\tPRIMARY KEY (lesson_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(vehicle_id) REFERENCES \"Vehicles\" (vehicle_id)\n)\n/\nColumns in Lessons and 3 examples in each column for high cardinality columns :\nlesson_id : 1, 13, 11\nlesson_date : 2018-03-03 15:10:16, 2018-03-07 16:12:36, 2018-03-08 16:05:05\nprice : 306.0, 492.0, 446.0\n/\n/\nColumns in Lessons and all categories for low cardinality columns :\ncustomer_id : 13, 11, 2, 5, 8, 6, 3, 10, 9\nlesson_status_code : Completed, Cancelled\nstaff_id : 1, 11, 5, 8, 4, 14, 3, 12, 15\nvehicle_id : 1, 2, 3\nlesson_time : 2, 5, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Asset_Parts\" (\n\tasset_id INTEGER NOT NULL, \n\tpart_id INTEGER NOT NULL, \n\tFOREIGN KEY(asset_id) REFERENCES \"Assets\" (asset_id), \n\tFOREIGN KEY(part_id) REFERENCES \"Parts\" (part_id)\n)\n/\nColumns in Asset_Parts and all categories for low cardinality columns :\nasset_id : 1, 2, 5, 15, 4, 6, 14, 3, 10\npart_id : 1, 2, 3\n/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n/\n\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE \"Papers\" (\n\t\"paperID\" INTEGER, \n\ttitle TEXT, \n\tPRIMARY KEY (\"paperID\")\n)\n/\nColumns in Papers and all categories for low cardinality columns :\npaperID : 201, 204, 205, 200, 206, 203, 202\ntitle : Nameless, Painless, Binders Unbound, Proving the Unique Fixed-Point Principle Correct: An Adventure with Category Theory, An Equivalence-Preserving CPS Translation via Multi-Language Semantics, Making Standard ML a Practical Database Programming Language, Functional Pearl: Modular Rollback through Control Logging, Just do it: Simple Monadic Equational Reasoning\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE \"CHECKING\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/\nColumns in CHECKING and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nbalance : 3000.0, 10000.0, 2000.0, 7.0, 7000.0, 77.0\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n/\n" }, { "role": "user", "content": "In zip code 94107, on which day neither Fog nor Rain was not observed?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, Fog, Rain.\nThe SQL query I'll be generating is:\nSELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != \"Fog\" AND EVENTS != \"Rain\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER, \n\tdate_formed DATETIME, \n\torganization_name VARCHAR(255), \n\tuk_vat_number VARCHAR(20), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 1, 2, 5, 4, 3\ndate_formed : 2016-08-24 23:52:48, 2016-07-28 01:45:10, 2016-10-09 07:22:53, 2017-04-06 23:59:16, 2016-10-01 12:42:01\norganization_name : Liberal Democrats, Green Party, Labour Party, Conservative, Plaid Cymru\nuk_vat_number : 2157, 1211, 7459, 7237, 4271\n/\n \nCREATE TABLE constructors (\n\t\"constructorId\" INTEGER, \n\t\"constructorRef\" TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"constructorId\")\n)\n/\nColumns in constructors and 3 examples in each column for high cardinality columns :\nconstructorId : 87, 56, 65\nconstructorRef : mf1, prost, lambo\nname : McLaren, Protos, Eagle-Climax\nnationality : Mexican, Russian, British\nurl : http://en.wikipedia.org/wiki/Minardi, http://en.wikipedia.org/wiki/Officine_Specializate_Costruzione_Automobili, http://en.wikipedia.org/wiki/Scirocco-Powell\n/\n\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Prescribes\" (\n\t\"Physician\" INTEGER NOT NULL, \n\t\"Patient\" INTEGER NOT NULL, \n\t\"Medication\" INTEGER NOT NULL, \n\t\"Date\" DATETIME NOT NULL, \n\t\"Appointment\" INTEGER, \n\t\"Dose\" VARCHAR(30) NOT NULL, \n\tPRIMARY KEY (\"Physician\", \"Patient\", \"Medication\", \"Date\"), \n\tCONSTRAINT \"fk_Prescribes_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Prescribes_Patient_SSN\" FOREIGN KEY(\"Patient\") REFERENCES \"Patient\" (\"SSN\"), \n\tCONSTRAINT \"fk_Prescribes_Medication_Code\" FOREIGN KEY(\"Medication\") REFERENCES \"Medication\" (\"Code\"), \n\tCONSTRAINT \"fk_Prescribes_Appointment_AppointmentID\" FOREIGN KEY(\"Appointment\") REFERENCES \"Appointment\" (\"AppointmentID\")\n)\n/\nColumns in Prescribes and all categories for low cardinality columns :\nPhysician : 1, 9\nPatient : 100000001, 100000004\nMedication : 1, 2\nDate : 2008-04-27 10:53:00, 2008-04-30 16:53:00, 2008-04-24 10:47:00\nAppointment : None, 86213939, 13216584\nDose : 10, 5\n/\n \nCREATE TABLE \"Functional_Areas\" (\n\tfunctional_area_code VARCHAR(15), \n\tparent_functional_area_code VARCHAR(15), \n\tfunctional_area_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (functional_area_code)\n)\n/\nColumns in Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\nparent_functional_area_code : 8\nfunctional_area_description : Keep blank, Signature, Acknowledgement\n/\n \nCREATE TABLE team (\n\t\"Team_id\" INTEGER, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Team_id\")\n)\n/\nColumns in team and all categories for low cardinality columns :\nTeam_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Enrique Osinski, Berneice Hand, Columbus Crew, Evalyn Feil, D.C. United, Anais VonRueden, Ryley Goldner, Miami Fusion, Los Angeles Galaxy, Brown Erdman\n/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n/\n/\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_quantity VARCHAR(80), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\norder_id : 13, 11, 5\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 13, 11, 2, 5, 4, 6, 12, 3, 15, 9\norder_quantity : 2, 5, 7, 8, 4, 3, 9, male\n/\n \nCREATE TABLE driver (\n\t\"Driver_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Home_city\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Driver_ID\")\n)\n/\nColumns in driver and 3 examples in each column for high cardinality columns :\nDriver_ID : 1, 11, 2\nName : Edwin Vargas, Henry Genga, Douglas McCrory\n/\n/\nColumns in driver and all categories for low cardinality columns :\nParty : Rep, Dem\nHome_city : Coventry, East Hartford, Hartford, Bethel, Manchester\nAge : 38, 45, 46, 37, 40, 36, 30, 52, 42, 35\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n/\n/\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_address_id INTEGER NOT NULL, \n\tnickname VARCHAR(80), \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tdate_joined_staff DATETIME, \n\tdate_left_staff DATETIME, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(staff_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nnickname : ymiller, weissnat.vincenzo, nicholaus92\nfirst_name : Jedidiah, Eulalia, Camylle\nmiddle_name : Clarabelle, Maiya, Ulices\nlast_name : Sawayn, Maggio, Kuphal\ndate_of_birth : 2005-05-02 06:23:36, 2003-01-16 06:29:11, 2007-06-11 20:03:28\ndate_joined_staff : 2017-08-27 19:19:44, 2017-04-27 03:21:26, 2016-06-06 08:54:28\ndate_left_staff : 2018-03-08 12:31:16, 2018-03-10 15:25:00, 2018-03-24 10:11:08\n/\n/\nColumns in Staff and all categories for low cardinality columns :\nstaff_address_id : 1, 3, 13, 2, 5, 7, 4, 6, 12, 14\n/\n \nCREATE TABLE \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_Type_Code\" CHAR(15), \n\t\"Workshop_Group_ID\" INTEGER NOT NULL, \n\t\"Product_Description\" VARCHAR(255), \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\t\"Other_Product_Service_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Service_ID\"), \n\tFOREIGN KEY(\"Workshop_Group_ID\") REFERENCES \"Drama_Workshop_Groups\" (\"Workshop_Group_ID\"), \n\tFOREIGN KEY(\"Service_Type_Code\") REFERENCES \"Ref_Service_Types\" (\"Service_Type_Code\"), \n\tUNIQUE (\"Service_ID\")\n)\n/\nColumns in Services and 3 examples in each column for high cardinality columns :\nService_ID : 219, 640, 630\nWorkshop_Group_ID : 954, 838, 431\nProduct_Price : 58932775.8822, 187358.6469, 2704.4719\n/\n/\nColumns in Services and all categories for low cardinality columns :\nService_Type_Code : 1, 2, 4, 3\nProduct_Description : None\nProduct_Name : photo, film, dinning\nOther_Product_Service_Details : None\n/\n" }, { "role": "user", "content": "On which day has it neither been foggy nor rained in the zip code of 94107?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, Fog, Rain.\nThe SQL query I'll be generating is:\nSELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != \"Fog\" AND EVENTS != \"Rain\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Companies\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value_billion\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Companies and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : PetroChina, Berkshire Hathaway, Petrobras\nSales_billion : 69.2, 189.6, 421.8\nProfits_billion : 16.4, 19.9, 17.4\nAssets_billion : 2467.9, 192.8, 1913.9\nMarket_Value_billion : 239.5, 186.5, 224.8\n/\n/\nColumns in Companies and all categories for low cardinality columns :\nHeadquarters : Spain, UK, China, Brazil, France, Russia, USA, Netherlands\nIndustry : Retailing, Conglomerate, Oil and gas, Telecommunications, Banking\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"driverStandings\" (\n\t\"driverStandingsId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\tpoints REAL, \n\tposition INTEGER, \n\t\"positionText\" TEXT, \n\twins INTEGER, \n\tPRIMARY KEY (\"driverStandingsId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/\nColumns in driverStandings and 3 examples in each column for high cardinality columns :\ndriverStandingsId : 87, 56, 65\ndriverId : 17, 21, 9\npoints : 8.0, 3.0, 29.0\nposition : 17, 21, 9\npositionText : 17, 21, 9\n/\n/\nColumns in driverStandings and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\nwins : 1, 2, 4, 3, 0\n/\n \nCREATE TABLE happy_hour_member (\n\t\"HH_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Total_amount\" REAL, \n\tPRIMARY KEY (\"HH_ID\", \"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in happy_hour_member and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4\nMember_ID : 5, 9, 3\nTotal_amount : 4.9, 4.2, 20.9, 16.9, 16.92, 20.92\n/\n \nCREATE TABLE station_company (\n\t\"Station_ID\" INTEGER, \n\t\"Company_ID\" INTEGER, \n\t\"Rank_of_the_Year\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\", \"Company_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES gas_station (\"Station_ID\")\n)\n/\nColumns in station_company and all categories for low cardinality columns :\nStation_ID : 1, 11, 7, 4, 6, 10\nCompany_ID : 1, 6, 3, 10, 9\nRank_of_the_Year : 1, 13, 2, 4, 3, 9\n/\n \nCREATE TABLE \"Grants\" (\n\tgrant_id INTEGER, \n\torganisation_id INTEGER NOT NULL, \n\tgrant_amount DECIMAL(19, 4) DEFAULT 0 NOT NULL, \n\tgrant_start_date DATETIME NOT NULL, \n\tgrant_end_date DATETIME NOT NULL, \n\tother_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (grant_id), \n\tFOREIGN KEY(organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/\nColumns in Grants and 3 examples in each column for high cardinality columns :\ngrant_id : 1, 13, 11\ngrant_amount : 24.7000, 1.9848, 0.0000\ngrant_start_date : 2016-11-20 00:18:51, 2011-05-10 22:44:08, 2015-12-14 13:02:11\ngrant_end_date : 2004-10-24 09:09:39, 1982-03-11 15:27:55, 2001-05-22 21:02:43\nother_details : aliquam, occaecati, qui\n/\n/\nColumns in Grants and all categories for low cardinality columns :\norganisation_id : 11, 2, 5, 7, 8, 14, 3, 12, 10, 9\n/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n/\n/\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\n/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : FM, PT, PP, CV, BK\nDocument_Type_Name : Book, Presentation, Paper, Film, CV\nDocument_Type_Description : fun, excellent, very good, good\n/\n" }, { "role": "user", "content": "What are the ids of stations that have latitude above 37.4 and never had bike availability below 7?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, lat, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE screen_mode (\n\t\"Graphics_mode\" REAL, \n\t\"Char_cells\" TEXT, \n\t\"Pixels\" TEXT, \n\t\"Hardware_colours\" REAL, \n\tused_kb REAL, \n\tmap TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"Graphics_mode\")\n)\n/\nColumns in screen_mode and all categories for low cardinality columns :\nGraphics_mode : 3.0, 1.0, 0.0, 2.0, 6.0, 4.0, 5.0\nChar_cells : 40 × 32, 20 × 32, 80 × 25, 40 × 25, 80 × 32\nPixels : 320 × 200, 640 × 200, 320 × 256, 640 × 256, 160 × 256\nHardware_colours : 8.0, 2.0, 4.0\nused_kb : 8.0, 10.0, 16.0, 20.0\nmap : 4000–7FFF, 3000–7FFF, 5800–7FFF, 6000–7FFF\nType : Text, Graphics\n/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Tasks\" (\n\ttask_id INTEGER, \n\tproject_id INTEGER NOT NULL, \n\ttask_details VARCHAR(255) NOT NULL, \n\t\"eg Agree Objectives\" VARCHAR(1), \n\tPRIMARY KEY (task_id), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/\nColumns in Tasks and 3 examples in each column for high cardinality columns :\ntask_id : 1, 13, 11\nproject_id : 1, 13, 11\ntask_details : t, m, q\n/\n/\nColumns in Tasks and all categories for low cardinality columns :\neg Agree Objectives : None\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Address\" TEXT, \n\t\"Num_of_staff\" TEXT, \n\t\"Score\" REAL, \n\t\"Open_Year\" TEXT, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/\nColumns in shop and all categories for low cardinality columns :\nShop_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAddress : 414 E. 12th Street, 324 E. 11th Street, 1330 Baltimore Street, 1201 Walnut Street, 909 Main Street, 1111 Main Street, 2345 McGee Street, 1200 Main Street, 1100 Main Street, 909 Walnut Street\nNum_of_staff : 16, 13, 28, 24, 34, 23, 19, 42, 27, 425\nScore : 36.0, 30.0, 42.0, 28.0, 38.0, 40.0, 32.0\nOpen_Year : 2008, 2010, 2011, 2006\n/\n \nCREATE TABLE \"STUDENT\" (\n\t\"STU_NUM\" INTEGER, \n\t\"STU_LNAME\" VARCHAR(15), \n\t\"STU_FNAME\" VARCHAR(15), \n\t\"STU_INIT\" VARCHAR(1), \n\t\"STU_DOB\" DATETIME, \n\t\"STU_HRS\" INTEGER, \n\t\"STU_CLASS\" VARCHAR(2), \n\t\"STU_GPA\" FLOAT, \n\t\"STU_TRANSFER\" NUMERIC, \n\t\"DEPT_CODE\" VARCHAR(18), \n\t\"STU_PHONE\" VARCHAR(4), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"STU_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n) \nCREATE TABLE \"Properties\" (\n\tproperty_id INTEGER NOT NULL, \n\tproperty_type_code CHAR(15) NOT NULL, \n\tproperty_address VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (property_id)\n)\n/\nColumns in Properties and 3 examples in each column for high cardinality columns :\nproperty_id : 120, 954, 108\nproperty_address : 5983 Fleta Throughway, 54591 Bernard Ridges Suite 864, 7713 Bode Burgs Apt. 113\n/\n/\nColumns in Properties and all categories for low cardinality columns :\nproperty_type_code : apartment, house, flat\nother_details : USA\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n/\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE \"Claims_Processing\" (\n\t\"Claim_Processing_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Claim_Outcome_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Staff_ID\" INTEGER, \n\tPRIMARY KEY (\"Claim_Processing_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Processing and 3 examples in each column for high cardinality columns :\nClaim_Processing_ID : 243, 342, 818\n/\n/\nColumns in Claims_Processing and all categories for low cardinality columns :\nClaim_ID : 45, 28, 90, 24, 34, 62, 15, 27, 81\nClaim_Outcome_Code : Settled, In progress, Disputed\nClaim_Stage_ID : 1, 3\nStaff_ID : 771, 427, 510, 673, 986, 687, 822, 589, 718\n/\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE \"Rating\" (\n\t\"rID\" INTEGER, \n\t\"mID\" INTEGER, \n\tstars INTEGER, \n\t\"ratingDate\" DATE, \n\tFOREIGN KEY(\"mID\") REFERENCES \"Movie\" (\"mID\"), \n\tFOREIGN KEY(\"rID\") REFERENCES \"Reviewer\" (\"rID\")\n)\n/\nColumns in Rating and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nmID : 108, 106, 103, 101, 104, 107\nstars : 2, 4, 5, 3\nratingDate : 2011-01-20, 2011-01-09, 2011-01-30, 2011-01-22, 2011-01-27, 2011-01-19, 2011-01-02, None, 2011-01-12, 2011-01-15\n/\n" }, { "role": "user", "content": "What are the ids of all stations that have a latitude above 37.4 and have never had less than 7 bikes available?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: id, lat, station_id, bikes_available.\nThe SQL query I'll be generating is:\nSELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE branch (\n\t\"Branch_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Open_year\" TEXT, \n\t\"Address_road\" TEXT, \n\t\"City\" TEXT, \n\tmembership_amount TEXT, \n\tPRIMARY KEY (\"Branch_ID\")\n)\n/\nColumns in branch and all categories for low cardinality columns :\nBranch_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Popert, Zytogorski, Alexandre, Brooke Greville, Taverner, Stanley, Saint Amant, Cochrane\nOpen_year : 2009, 2013, 2015, 2001, 2012, 2014\nAddress_road : Abbott Street, Concord Road, Brampton Road, Cecilia Avenue, Oaks Crescent, Valleys Place, Glebe Street, Abbey Rise\nCity : Oxford, London\nmembership_amount : 91, 56, 11, 1418, 7, 6, 112, 31\n/\n \nCREATE TABLE \"Stores\" (\n\t\"Store_ID\" VARCHAR(100) NOT NULL, \n\t\"Address_ID\" INTEGER NOT NULL, \n\t\"Marketing_Region_Code\" CHAR(15) NOT NULL, \n\t\"Store_Name\" VARCHAR(255), \n\t\"Store_Phone\" VARCHAR(255), \n\t\"Store_Email_Address\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Store_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tFOREIGN KEY(\"Marketing_Region_Code\") REFERENCES \"Marketing_Regions\" (\"Marketing_Region_Code\"), \n\tUNIQUE (\"Store_ID\")\n)\n/\nColumns in Stores and all categories for low cardinality columns :\nStore_ID : 518, 229, 150, 236, 291, 444, 231, 512, 421, 344\nAddress_ID : 230, 110, 192, 266, 286, 74, 369\nMarketing_Region_Code : FR, IN, CN, ES, RU, CA\nStore_Name : Rob Dinning, Fred Dinning, FJA Filming, Carmol Photo, Ewi Filming, Adam Photo, Shery Photo, Lur Photo, Adan Dinning, FK Filming\nStore_Phone : +65(1)3590790358, 127.870.0753x54565, (941)444-7666x7089, 896-931-9633x869, 086-705-8793, 893-457-3102x4293, 605-319-8245, +46(1)1411714927, 1-678-902-9434x1148, 1-327-185-9368\nStore_Email_Address : fkuvalis@example.net, frederik37@example.org, rborer@example.org, carmel04@example.com, adams.miles@example.net, ewisoky@example.org, shirley07@example.net, adan93@example.com, lurline24@example.org, fjacobson@example.com\nOther_Details : None, 5 stars, 3 stars, 4 stars\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Ref_Calendar\" (\n\t\"Calendar_Date\" DATETIME NOT NULL, \n\t\"Day_Number\" INTEGER, \n\tPRIMARY KEY (\"Calendar_Date\")\n)\n/\nColumns in Ref_Calendar and 3 examples in each column for high cardinality columns :\nCalendar_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1972-03-31 09:47:22\n/\n/\nColumns in Ref_Calendar and all categories for low cardinality columns :\nDay_Number : 1, 2, 5, 7, 8, 3, 9\n/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n/\n \nCREATE TABLE member_attendance (\n\t\"Member_ID\" INTEGER, \n\t\"Performance_ID\" INTEGER, \n\t\"Num_of_Pieces\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Performance_ID\"), \n\tFOREIGN KEY(\"Performance_ID\") REFERENCES performance (\"Performance_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in member_attendance and all categories for low cardinality columns :\nMember_ID : 1, 11, 2, 5, 7, 4, 3\nPerformance_ID : 1, 2, 4, 6, 3\nNum_of_Pieces : 1, 2, 4, 3\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE \"Complaints\" (\n\tcomplaint_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tcomplaint_outcome_code VARCHAR(20) NOT NULL, \n\tcomplaint_status_code VARCHAR(20) NOT NULL, \n\tcomplaint_type_code VARCHAR(20) NOT NULL, \n\tdate_complaint_raised DATETIME, \n\tdate_complaint_closed DATETIME, \n\tstaff_id INTEGER NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Complaints and 3 examples in each column for high cardinality columns :\ncomplaint_id : 1, 11, 2\n/\n/\nColumns in Complaints and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\ncustomer_id : 120, 114, 113, 116, 117, 115, 118\ncomplaint_outcome_code : OK\ncomplaint_status_code : Open, Closed, New\ncomplaint_type_code : Product Failure, Product Unusable\ndate_complaint_raised : 2006-10-29 07:08:46, 2002-07-18 10:59:35, 1977-08-06 00:31:19, 1987-07-11 14:40:30, 1973-02-10 22:55:56, 2007-10-14 21:50:43\ndate_complaint_closed : 2013-09-14 02:59:10, 1975-10-11 05:54:30, 1970-10-14 00:57:25, 1976-04-19 11:03:06, 1995-09-11 14:48:46, 2000-08-17 17:02:48\nstaff_id : 120, 114, 116, 117, 115, 118\n/\n" }, { "role": "user", "content": "What are names of stations that have average bike availability above 10 and are not located in San Jose city?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, bikes_available, name, city, San Jose.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = \"San Jose\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Photos\" (\n\t\"Photo_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Filename\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Photo_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Photos and 3 examples in each column for high cardinality columns :\nPhoto_ID : 428, 303, 332\nTourist_Attraction_ID : 5076, 6523, 5265\nName : fun3, din2, park1\nFilename : 863, 695, 392\n/\n/\nColumns in Photos and all categories for low cardinality columns :\nDescription : None\nOther_Details : None\n/\n \nCREATE TABLE competition_record (\n\t\"Competition_ID\" INTEGER, \n\t\"Farm_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Competition_ID\", \"Farm_ID\"), \n\tFOREIGN KEY(\"Farm_ID\") REFERENCES farm (\"Farm_ID\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES farm_competition (\"Competition_ID\")\n)\n/\nColumns in competition_record and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 3\nFarm_ID : 1, 2, 5, 7, 8, 4, 3\nRank : 1, 2, 4, 3\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n/\n\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n/\n \nCREATE TABLE \"Trained_In\" (\n\t\"Physician\" INTEGER NOT NULL, \n\t\"Treatment\" INTEGER NOT NULL, \n\t\"CertificationDate\" DATETIME NOT NULL, \n\t\"CertificationExpires\" DATETIME NOT NULL, \n\tPRIMARY KEY (\"Physician\", \"Treatment\"), \n\tCONSTRAINT \"fk_Trained_In_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Trained_In_Procedures_Code\" FOREIGN KEY(\"Treatment\") REFERENCES \"Procedures\" (\"Code\")\n)\n/\nColumns in Trained_In and all categories for low cardinality columns :\nPhysician : 7, 6, 3\nTreatment : 1, 2, 5, 7, 4, 6, 3\nCertificationDate : 2008-01-01 00:00:00, 2007-01-01 00:00:00\nCertificationExpires : 2007-12-31 00:00:00, 2008-12-31 00:00:00\n/\n \nCREATE TABLE teachers (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/\nColumns in teachers and 3 examples in each column for high cardinality columns :\nLastName : MOYER, NIBLER, ONDERSMA\nFirstName : CHARMAINE, JEROME, KIRK\nClassroom : 109, 108, 106\n/\n\n \nCREATE TABLE \"Images\" (\n\timage_id INTEGER, \n\timage_alt_text VARCHAR(80), \n\timage_name VARCHAR(40), \n\timage_url VARCHAR(255), \n\tPRIMARY KEY (image_id)\n)\n/\nColumns in Images and 3 examples in each column for high cardinality columns :\nimage_id : 1, 13, 11\nimage_alt_text : Chaya, Ashtyn, Marianna\nimage_name : chapter3, data1, data2\nimage_url : http://www.bernierconnelly.com/1.jpg, http://www.hermann.com/1.jpg, http://connellykertzmann.org/1.jpg\n/\n\n \nCREATE TABLE regions (\n\t\"REGION_ID\" DECIMAL(5, 0) NOT NULL, \n\t\"REGION_NAME\" VARCHAR(25) DEFAULT NULL, \n\tPRIMARY KEY (\"REGION_ID\")\n)\n/\nColumns in regions and all categories for low cardinality columns :\nREGION_ID : 1, 2, 4, 3\nREGION_NAME : Europe\\r, Middle East and Africa\\r, Asia\\r, Americas\\r\n/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n/\n \nCREATE TABLE \"Projects\" (\n\t\"Project_ID\" INTEGER NOT NULL, \n\t\"Project_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Project_ID\")\n)\n/\nColumns in Projects and all categories for low cardinality columns :\nProject_ID : 35, 30, 134, 105, 195\nProject_Details : Graph Database project, Internet of Things project, Population Research project, Society Research project, Human Resource project\n/\n \nCREATE TABLE \"Ref_Transaction_Types\" (\n\ttransaction_type_code VARCHAR(10), \n\ttransaction_type_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (transaction_type_code)\n)\n/\nColumns in Ref_Transaction_Types and all categories for low cardinality columns :\ntransaction_type_code : PUR, SALE\ntransaction_type_description : Sale, Purchase\n/\n" }, { "role": "user", "content": "What are the names of all stations that have more than 10 bikes available and are not located in San Jose?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, status.\nFrom these tables, I'll be using the following columns: station.name, station.id, status.station_id, bikes_available, name, city, San Jose.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = \"San Jose\"" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Performance\" (\n\t\"SongId\" INTEGER, \n\t\"Bandmate\" INTEGER, \n\t\"StagePosition\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"Bandmate\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"Bandmate\") REFERENCES \"Band\" (\"Id\")\n)\n/\nColumns in Performance and all categories for low cardinality columns :\nSongId : \nBandmate : \nStagePosition : \n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n \nCREATE TABLE dependent (\n\t\"Essn\" INTEGER, \n\t\"Dependent_name\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Bdate\" TEXT, \n\t\"Relationship\" TEXT, \n\tPRIMARY KEY (\"Essn\", \"Dependent_name\")\n)\n/\nColumns in dependent and all categories for low cardinality columns :\nEssn : 333445555, 123456789, 987654321\nDependent_name : Alice, Michael, Theodore, Abner, Joy, Elizabeth\nSex : F, M\nBdate : 1986-04-05, 1988-01-04, 1967-05-05, 1983-10-25, 1958-05-03, 1942-02-28, 1988-12-30\nRelationship : Daughter, Son, Spouse\n/\n \nCREATE TABLE \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\n\n \nCREATE TABLE \"Dorm_amenity\" (\n\tamenid INTEGER, \n\tamenity_name VARCHAR(25)\n)\n/\nColumns in Dorm_amenity and 3 examples in each column for high cardinality columns :\namenid : 922, 955, 900\namenity_name : Study Room, Allows Pets, Roof\n/\n\n \nCREATE TABLE entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n/\n \nCREATE TABLE \"Transactions_Lots\" (\n\ttransaction_id INTEGER NOT NULL, \n\tlot_id INTEGER NOT NULL, \n\tFOREIGN KEY(transaction_id) REFERENCES \"Transactions\" (transaction_id), \n\tFOREIGN KEY(lot_id) REFERENCES \"Lots\" (lot_id)\n)\n/\nColumns in Transactions_Lots and all categories for low cardinality columns :\ntransaction_id : 1, 2, 15, 7, 6, 12, 3, 14, 10\nlot_id : 1, 11, 15, 8, 4, 14, 3, 10, 9\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 1, 2, 3\nproduct_details : Dove Chocolate, Americano, Latte\n/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n/\n \nCREATE TABLE stadium (\n\tid INTEGER, \n\tname TEXT, \n\t\"Home_Games\" INTEGER, \n\t\"Average_Attendance\" REAL, \n\t\"Total_Attendance\" REAL, \n\t\"Capacity_Percentage\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in stadium and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Gillette Stadium, Lincoln Financial Field, New Meadowlands Stadium\nAverage_Attendance : 70038.0, 87047.0, 71227.0\nTotal_Attendance : 553144.0, 566362.0, 550048.0\n/\n/\nColumns in stadium and all categories for low cardinality columns :\nHome_Games : 8\nCapacity_Percentage : 96.0, 108.8, 100.3, 100.0, 95.8, 90.7, 102.3, 98.4, 97.1, 95.3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n" }, { "role": "user", "content": "What are the name, latitude, and city of the station with the lowest latitude?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: name, lat, city.\nThe SQL query I'll be generating is:\nSELECT name , lat , city FROM station ORDER BY lat LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Customer_Events\" (\n\t\"Customer_Event_ID\" INTEGER NOT NULL, \n\tcustomer_id INTEGER, \n\tdate_moved_in DATETIME, \n\tproperty_id INTEGER, \n\tresident_id INTEGER, \n\tthing_id INTEGER NOT NULL, \n\tPRIMARY KEY (\"Customer_Event_ID\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(resident_id, property_id, date_moved_in) REFERENCES \"Residents\" (resident_id, property_id, date_moved_in)\n)\n/\nColumns in Customer_Events and 3 examples in each column for high cardinality columns :\nCustomer_Event_ID : 428, 216, 226\nresident_id : 87, 38, 37\n/\n/\nColumns in Customer_Events and all categories for low cardinality columns :\ncustomer_id : 79, 91, 16, 5, 4, 63, 19, 31\ndate_moved_in : 2016-09-27 12:00:00, 2015-03-27 12:00:00\nproperty_id : 954, 120, 108, 605, 629, 748, 669, 445, 879, 107\nthing_id : 1, 46, 10, 80, 2, 92, 14, 85, 68\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE \"Participants_in_Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Participant_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\", \"Participant_ID\"), \n\tFOREIGN KEY(\"Participant_ID\") REFERENCES \"Participants\" (\"Participant_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/\nColumns in Participants_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n/\n/\nColumns in Participants_in_Events and all categories for low cardinality columns :\nParticipant_ID : 26, 86, 37, 90, 36, 96, 66, 63, 60, 64\n/\n \nCREATE TABLE endowment (\n\tendowment_id INTEGER, \n\t\"School_id\" INTEGER, \n\tdonator_name TEXT, \n\tamount REAL, \n\tPRIMARY KEY (endowment_id), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in endowment and 3 examples in each column for high cardinality columns :\nendowment_id : 1, 11, 2\ndonator_name : Santo Domingo Este, Duarte, San Cristóbal\namount : 9.05, 8.82, 8.85\n/\n/\nColumns in endowment and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Invoice_Items\" (\n\t\"Invoice_Item_ID\" INTEGER NOT NULL, \n\t\"Invoice_ID\" INTEGER NOT NULL, \n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Order_Item_ID\" INTEGER NOT NULL, \n\t\"Product_ID\" INTEGER NOT NULL, \n\t\"Order_Quantity\" INTEGER, \n\t\"Other_Item_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Invoice_Item_ID\"), \n\tFOREIGN KEY(\"Order_Item_ID\") REFERENCES \"Order_Items\" (\"Order_Item_ID\"), \n\tFOREIGN KEY(\"Invoice_ID\") REFERENCES \"Invoices\" (\"Invoice_ID\"), \n\tFOREIGN KEY(\"Order_ID\", \"Product_ID\") REFERENCES \"Bookings_Services\" (\"Order_ID\", \"Product_ID\")\n)\n/\nColumns in Invoice_Items and all categories for low cardinality columns :\nInvoice_Item_ID : 1, 2\nInvoice_ID : 128, 162\nOrder_ID : 1, 4\nOrder_Item_ID : 5, 6\nProduct_ID : 396, 191\nOrder_Quantity : 2, 6\nOther_Item_Details : None, Good quality\n/\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id)\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\naccount_name : 866, 725, 858\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 2, 8, 4, 6, 12, 14, 10, 9\nother_account_details : VIP, Regular\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Agreements\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/\nColumns in Agreements and 3 examples in each column for high cardinality columns :\nDocument_ID : 1, 13, 11\n/\n/\nColumns in Agreements and all categories for low cardinality columns :\nEvent_ID : 13, 11, 10, 5, 8, 6, 12, 15, 9\n/\n \nCREATE TABLE \"Staff_Department_Assignments\" (\n\tstaff_id INTEGER NOT NULL, \n\tdepartment_id INTEGER NOT NULL, \n\tdate_assigned_from DATETIME NOT NULL, \n\tjob_title_code VARCHAR(10) NOT NULL, \n\tdate_assigned_to DATETIME, \n\tPRIMARY KEY (staff_id, department_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(department_id) REFERENCES \"Departments\" (department_id)\n)\n/\nColumns in Staff_Department_Assignments and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 2, 5\ndate_assigned_from : 2016-06-24 17:31:24, 2016-09-20 02:59:15, 2017-06-11 22:55:20\ndate_assigned_to : 2018-03-25 03:15:31, 2018-03-24 09:11:14, 2018-03-25 15:34:31\n/\n/\nColumns in Staff_Department_Assignments and all categories for low cardinality columns :\ndepartment_id : 1, 2, 5, 4, 3\njob_title_code : Sales Person, Administration, Clerical Staff, Department Manager\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_first_name VARCHAR(20), \n\tcustomer_last_name VARCHAR(20), \n\tcustomer_address VARCHAR(255), \n\tcustomer_phone VARCHAR(255), \n\tcustomer_email VARCHAR(255), \n\tother_customer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_first_name : Armani, Bryce, Nat\ncustomer_last_name : Swift, Lind, Huels\ncustomer_address : 6478 Moen Isle Suite 910\nSchimmelmouth, VT 96364-4898, 47286 Mraz Park Apt. 424\nJocelynfurt, OH 59023-2787, 094 Julianne Mill\nWebstertown, KY 91980-4004\ncustomer_phone : (415)237-0701x3115, 679-845-8645x94312, 284.749.0453\ncustomer_email : kyra.murazik@example.org, schaden.katrina@example.net, huels.antonina@example.com\n/\n/\nColumns in Customers and all categories for low cardinality columns :\nother_customer_details : None\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n" }, { "role": "user", "content": "What is the name, latitude, and city of the station that is located the furthest South?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: name, lat, city.\nThe SQL query I'll be generating is:\nSELECT name , lat , city FROM station ORDER BY lat LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Fault_Log\" (\n\tfault_log_entry_id INTEGER, \n\tasset_id INTEGER NOT NULL, \n\trecorded_by_staff_id INTEGER NOT NULL, \n\tfault_log_entry_datetime DATETIME, \n\tfault_description VARCHAR(255), \n\tother_fault_details VARCHAR(255), \n\tPRIMARY KEY (fault_log_entry_id), \n\tFOREIGN KEY(recorded_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(asset_id) REFERENCES \"Assets\" (asset_id)\n)\n/\nColumns in Fault_Log and 3 examples in each column for high cardinality columns :\nfault_log_entry_id : 1, 13, 11\nfault_log_entry_datetime : 2018-03-01 08:52:58, 2018-02-28 02:07:36, 2018-03-13 09:43:05\n/\n/\nColumns in Fault_Log and all categories for low cardinality columns :\nasset_id : 2, 5, 7, 8, 6, 12, 3, 15, 9\nrecorded_by_staff_id : 13, 11, 5, 8, 4, 14, 12, 10, 9\nfault_description : failed parts, system error\nother_fault_details : None\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n/\n/\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n/\n \nCREATE TABLE region (\n\t\"Region_ID\" INTEGER, \n\t\"Region_name\" TEXT, \n\t\"Date\" TEXT, \n\t\"Label\" TEXT, \n\t\"Format\" TEXT, \n\t\"Catalogue\" TEXT, \n\tPRIMARY KEY (\"Region_ID\")\n)\n/\nColumns in region and all categories for low cardinality columns :\nRegion_ID : 1, 2, 5, 4, 3\nRegion_name : Japan, United Kingdom, United States\nDate : 1 July 2002, 16 July 2002, 3 July 2002\nLabel : Toshiba-EMI, Astralwerks, Parlophone\nFormat : CD digipak, 2× LP, CD\nCatalogue : ASW 40362, ASW 40522, 539 9821, TOCP-66045, 540 3622\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE qualifying (\n\t\"qualifyId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tnumber INTEGER, \n\tposition INTEGER, \n\tq1 TEXT, \n\tq2 TEXT, \n\tq3 TEXT, \n\tPRIMARY KEY (\"qualifyId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/\nColumns in qualifying and 3 examples in each column for high cardinality columns :\nqualifyId : 87, 56, 65\ndriverId : 19, 17, 21\nconstructorId : 1, 11, 2\nnumber : 19, 17, 21\nposition : 17, 21, 9\nq1 : , 1:17.053, 1:16.933\nq2 : , 1:32.915, 1:20.894\nq3 : NULL, 1:35.748, 1:17.343\n/\n/\nColumns in qualifying and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\n/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n/\n \nCREATE TABLE \"Customer_Address_History\" (\n\tcustomer_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME NOT NULL, \n\tdate_to DATETIME, \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Address_History and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 10\ndate_from : 2009-02-16 23:04:20, 2008-06-22 21:50:44, 2011-01-02 21:42:29\ndate_to : 2018-03-20 01:13:38, 2018-03-11 20:16:56, 2018-03-24 06:20:36\n/\n/\nColumns in Customer_Address_History and all categories for low cardinality columns :\ncustomer_id : 13, 11, 2, 7, 6, 12, 3, 14, 9\n/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n/\n \nCREATE TABLE \"Member_of\" (\n\t\"FacID\" INTEGER, \n\t\"DNO\" INTEGER, \n\t\"Appt_Type\" VARCHAR(15), \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Member_of and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\n/\n/\nColumns in Member_of and all categories for low cardinality columns :\nDNO : 50, 550, 520, 600\nAppt_Type : Secondary, Primary\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE school_performance (\n\t\"School_Id\" INTEGER, \n\t\"School_Year\" TEXT, \n\t\"Class_A\" TEXT, \n\t\"Class_AA\" TEXT, \n\tPRIMARY KEY (\"School_Id\", \"School_Year\"), \n\tFOREIGN KEY(\"School_Id\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_performance and 3 examples in each column for high cardinality columns :\nSchool_Year : 1998-99, 2002-03, 1994-95\nClass_A : Skidmore-Tynan, Lindsay, Anton\nClass_AA : Buffalo, Henrietta, S&S Consolidated\n/\n/\nColumns in school_performance and all categories for low cardinality columns :\nSchool_Id : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n/\n" }, { "role": "user", "content": "What are the date, mean temperature and mean humidity for the top 3 days with the largest max gust speeds?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, mean_temperature_f, mean_humidity, max_gust_speed_mph.\nThe SQL query I'll be generating is:\nSELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n/\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n/\n \nCREATE TABLE technician (\n\ttechnician_id REAL, \n\t\"Name\" TEXT, \n\t\"Team\" TEXT, \n\t\"Starting_Year\" REAL, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (technician_id)\n)\n/\nColumns in technician and all categories for low cardinality columns :\ntechnician_id : 3.0, 8.0, 10.0, 1.0, 7.0, 2.0, 6.0, 9.0, 4.0, 5.0\nName : Mark Sewell, John Brown, Mickey Cochrane, Joe Sewell, Tony Sewell, Joe Cochrane, Eddie Collins, Charlie Hollocher, Lou Boudreau\nTeam : CHC, NYY, CLE, PHA, CWS\nStarting_Year : 2013.0, 2016.0, 2003.0, 2006.0, 2005.0, 2002.0, 2009.0, 2012.0\nAge : 38, 37, 45, 46, 28, 36, 32, 47, 43, 35\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE aircraft (\n\t\"Aircraft_ID\" INTEGER NOT NULL, \n\t\"Aircraft\" VARCHAR(50) NOT NULL, \n\t\"Description\" VARCHAR(50) NOT NULL, \n\t\"Max_Gross_Weight\" VARCHAR(50) NOT NULL, \n\t\"Total_disk_area\" VARCHAR(50) NOT NULL, \n\t\"Max_disk_Loading\" VARCHAR(50) NOT NULL, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 4, 3\nAircraft : Bell 206B3 JetRanger, Mil Mi-26, CH-53E Super Stallion, Robinson R-22, CH-47D Chinook\nDescription : Light utility helicopter, Heavy-lift helicopter, Turboshaft utility helicopter, Tandem rotor helicopter\nMax_Gross_Weight : 50,000 lb (22,680 kg), 123,500 lb (56,000 kg), 73,500 lb (33,300 kg), 3,200 lb (1,451 kg), 1,370 lb (635 kg)\nTotal_disk_area : 872 ft² (81.1 m²), 5,655 ft² (526 m²), 8,495 ft² (789 m²), 497 ft² (46.2 m²), 4,900 ft² (460 m²)\nMax_disk_Loading : 15 lb/ft² (72 kg/m²), 2.6 lb/ft² (14 kg/m²), 14.5 lb/ft² (71 kg/m²), 8.8 lb/ft² (43 kg/m²), 3.7 lb/ft² (18 kg/m²)\n/\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n/\n \nCREATE TABLE \"Problems\" (\n\tproblem_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\tclosure_authorised_by_staff_id INTEGER NOT NULL, \n\treported_by_staff_id INTEGER NOT NULL, \n\tdate_problem_reported DATETIME NOT NULL, \n\tdate_problem_closed DATETIME, \n\tproblem_description VARCHAR(255), \n\tother_problem_details VARCHAR(255), \n\tPRIMARY KEY (problem_id), \n\tFOREIGN KEY(reported_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Product\" (product_id), \n\tFOREIGN KEY(closure_authorised_by_staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Problems and 3 examples in each column for high cardinality columns :\nproblem_id : 1, 13, 11\nclosure_authorised_by_staff_id : 1, 13, 2\ndate_problem_reported : 1995-05-14 08:32:56, 1988-11-07 16:09:31, 1986-11-13 07:30:55\ndate_problem_closed : 1974-09-20 13:42:19, 1997-10-18 20:09:57, 2004-06-20 01:08:25\nproblem_description : d, i, s\n/\n/\nColumns in Problems and all categories for low cardinality columns :\nproduct_id : 1, 13, 2, 5, 7, 8, 4, 6, 15\nreported_by_staff_id : 1, 13, 11, 2, 5, 7, 4, 14, 10\nother_problem_details : f, m, i, s, k, l, p, v, c\n/\n \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15), \n\tproduct_name VARCHAR(80), \n\tproduct_price DOUBLE, \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_price : 5927021.8748021, 622.79275984494, 22956668.699482\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Hardware, Clothes\nproduct_name : Apple, jcrew, Sony, gucci\n/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n/\n/\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What is the date, average temperature and mean humidity for the days with the 3 largest maximum gust speeds?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, mean_temperature_f, mean_humidity, max_gust_speed_mph.\nThe SQL query I'll be generating is:\nSELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE roller_coaster (\n\t\"Roller_Coaster_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Park\" TEXT, \n\t\"Country_ID\" INTEGER, \n\t\"Length\" REAL, \n\t\"Height\" REAL, \n\t\"Speed\" TEXT, \n\t\"Opened\" TEXT, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (\"Roller_Coaster_ID\"), \n\tFOREIGN KEY(\"Country_ID\") REFERENCES country (\"Country_ID\")\n)\n/\nColumns in roller_coaster and all categories for low cardinality columns :\nRoller_Coaster_ID : 1, 2, 5, 4, 6, 3\nName : The Voyage, Twister, Boardwalk Bullet, Hades 360, Dauling Dragon, Ravine Flyer II\nPark : Waldameer, Happy Valley, Mt. Olympus, Gröna Lund, Kemah Boardwalk, Holiday World\nCountry_ID : 1, 2, 3\nLength : 6442.0, 4726.0, 3236.0, 1574.0, 2900.0, 3914.0\nHeight : 96.0, 105.0, 136.0, 50.0, 120.0, 163.0\nSpeed : 67, 55, 37.9, 70, 57, 51\nOpened : May 14, 2005, 2012, August 31, 2007, 2011, May 6, 2006, May 17, 2008\nStatus : Operating\n/\n \nCREATE TABLE \"Parking_Fines\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Parking_Fines and all categories for low cardinality columns :\ncouncil_tax_id : 10, 9\ncmi_cross_ref_id : 4, 81\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Customers_Cards\" (\n\tcard_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tcard_type_code VARCHAR(15) NOT NULL, \n\tcard_number VARCHAR(80), \n\tdate_valid_from DATETIME, \n\tdate_valid_to DATETIME, \n\tother_card_details VARCHAR(255), \n\tPRIMARY KEY (card_id)\n)\n/\nColumns in Customers_Cards and 3 examples in each column for high cardinality columns :\ncard_id : 1, 13, 11\ncustomer_id : 3, 13, 10\ncard_number : 4560596484842, 4716674779726, 348237249146948\ndate_valid_from : 2013-05-23 07:55:36, 2012-05-22 02:05:41, 2013-11-17 02:58:22\ndate_valid_to : 2018-03-14 14:00:07, 2018-03-12 02:16:45, 2018-03-24 00:38:54\nother_card_details : 6011771512810699, 4916493714393, 5428692691195935\n/\n/\nColumns in Customers_Cards and all categories for low cardinality columns :\ncard_type_code : Credit, Debit\n/\n \nCREATE TABLE \"Catalogs\" (\n\tcatalog_id INTEGER, \n\tcatalog_name VARCHAR(50), \n\tcatalog_publisher VARCHAR(80), \n\tdate_of_publication DATETIME, \n\tdate_of_latest_revision DATETIME, \n\tPRIMARY KEY (catalog_id)\n)\n/\nColumns in Catalogs and all categories for low cardinality columns :\ncatalog_id : 1, 2, 5, 7, 8, 4, 6, 3\ncatalog_name : Coffee Bean, Latte, Sparkling Water, Breakfast Tea, Jam, Lemonade, Chocolate, Coco powder\ncatalog_publisher : Russel-Gislason Lemon shop, Lidl, Koepp-Rutherford handmade chocolate store, Murray Coffee shop, Grady & Kautzer\ndate_of_publication : 2012-04-13 06:37:09, 2011-07-22 04:57:19, 2013-03-15 05:09:17, 2012-11-27 19:29:22\ndate_of_latest_revision : 2017-03-30 09:15:37, 2017-10-26 01:16:51, 2017-09-26 12:10:36, 2017-12-04 06:48:13\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n/\n/\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id)\n)\n/\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\nproduct_id : 13, 11, 2\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\norder_id : 1, 13, 5, 7, 8, 6, 14, 12, 15, 9\n/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n" }, { "role": "user", "content": "List the name and the number of stations for all the cities that have at least 15 stations." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city.\nThe SQL query I'll be generating is:\nSELECT city , COUNT() FROM station GROUP BY city HAVING COUNT() >= 15" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Documents\" (\n\tdocument_code VARCHAR(15), \n\tdocument_structure_code VARCHAR(15) NOT NULL, \n\tdocument_type_code VARCHAR(15) NOT NULL, \n\taccess_count INTEGER, \n\tdocument_name VARCHAR(80), \n\tPRIMARY KEY (document_code), \n\tFOREIGN KEY(document_structure_code) REFERENCES \"Document_Structures\" (document_structure_code)\n)\n/\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_code : 510, 714, 217\naccess_count : 8208, 3289, 2294\ndocument_name : Learning English, Summer Sails, Learning Database\n/\n/\nColumns in Documents and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\ndocument_type_code : Book, Advertisement, CV, Paper\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE \"Member_of\" (\n\t\"FacID\" INTEGER, \n\t\"DNO\" INTEGER, \n\t\"Appt_Type\" VARCHAR(15), \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Member_of and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\n/\n/\nColumns in Member_of and all categories for low cardinality columns :\nDNO : 50, 550, 520, 600\nAppt_Type : Secondary, Primary\n/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n/\n \nCREATE TABLE \"Authorship\" (\n\t\"authID\" INTEGER, \n\t\"instID\" INTEGER, \n\t\"paperID\" INTEGER, \n\t\"authOrder\" INTEGER, \n\tPRIMARY KEY (\"authID\", \"instID\", \"paperID\"), \n\tFOREIGN KEY(\"authID\") REFERENCES \"Authors\" (\"authID\"), \n\tFOREIGN KEY(\"instID\") REFERENCES \"Inst\" (\"instID\"), \n\tFOREIGN KEY(\"paperID\") REFERENCES \"Papers\" (\"paperID\")\n)\n/\nColumns in Authorship and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\n/\n/\nColumns in Authorship and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\npaperID : 201, 204, 205, 200, 206, 203, 202\nauthOrder : 1, 2, 3\n/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n/\n \nCREATE TABLE medicine_enzyme_interaction (\n\tenzyme_id INTEGER, \n\tmedicine_id INTEGER, \n\tinteraction_type TEXT, \n\tPRIMARY KEY (enzyme_id, medicine_id), \n\tFOREIGN KEY(medicine_id) REFERENCES medicine (id), \n\tFOREIGN KEY(enzyme_id) REFERENCES enzyme (id)\n)\n/\nColumns in medicine_enzyme_interaction and 3 examples in each column for high cardinality columns :\nmedicine_id : 1, 13, 20\n/\n/\nColumns in medicine_enzyme_interaction and all categories for low cardinality columns :\nenzyme_id : 1, 2, 5, 4, 6, 3\ninteraction_type : inhibitor, activitor\n/\n \nCREATE TABLE \"School\" (\n\t\"School_id\" TEXT, \n\t\"School_name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Mascot\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"IHSAA_Class\" TEXT, \n\t\"IHSAA_Football_Class\" TEXT, \n\t\"County\" TEXT, \n\tPRIMARY KEY (\"School_id\")\n)\n/\nColumns in School and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\nSchool_name : New Prairie 1, Triton, LaVille, Glenn, Culver Community, Jimtown, Knox Community, Bremen\nLocation : Bourbon, Walkerton, Lakeville, Knox, Culver, New Carlisle, Elkhart, Bremen\nMascot : Lancers, Cougars, Cavaliers, Trojans, Redskins, Falcons, Lions, Jimmies\nEnrollment : 601, 605, 287, 495, 620, 379, 852, 316\nIHSAA_Class : AA, A, AAA\nIHSAA_Football_Class : AA, A, AAA, AAAA\nCounty : 20 Elkhart, 50 Marshall, 75 Starke, 71 St. Joseph, 46 LaPorte 71 St. Joseph\n/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n/\n" }, { "role": "user", "content": "What is the name of every city that has at least 15 stations and how many stations does it have?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city.\nThe SQL query I'll be generating is:\nSELECT city , COUNT() FROM station GROUP BY city HAVING COUNT() >= 15" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Genre\" (\n\t\"GenreId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"GenreId\")\n)\n/\nColumns in Genre and 3 examples in each column for high cardinality columns :\nGenreId : 17, 21, 9\nName : Bossa Nova, Comedy, Opera\n/\n\n \nCREATE TABLE \"Performers_in_Bookings\" (\n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Performer_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Order_ID\", \"Performer_ID\"), \n\tFOREIGN KEY(\"Performer_ID\") REFERENCES \"Performers\" (\"Performer_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Bookings\" (\"Booking_ID\")\n)\n/\nColumns in Performers_in_Bookings and 3 examples in each column for high cardinality columns :\nPerformer_ID : 153, 656, 954\n/\n/\nColumns in Performers_in_Bookings and all categories for low cardinality columns :\nOrder_ID : 1, 13, 11, 2, 7, 8, 4, 3, 15, 9\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Settlements\" (\n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Date_Claim_Made\" DATE, \n\t\"Date_Claim_Settled\" DATE, \n\t\"Amount_Claimed\" INTEGER, \n\t\"Amount_Settled\" INTEGER, \n\t\"Customer_Policy_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Settlement_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claims\" (\"Claim_ID\")\n)\n/\nColumns in Settlements and 3 examples in each column for high cardinality columns :\nSettlement_ID : 756, 616, 527\nDate_Claim_Made : 2017-05-19, 2016-09-05, 2018-05-12\nDate_Claim_Settled : 2017-12-24, 2017-11-15, 2018-02-20\nAmount_Claimed : 37302, 20569, 25078\nAmount_Settled : 1676, 1181, 930\nCustomer_Policy_ID : 943, 839, 590\n/\n/\nColumns in Settlements and all categories for low cardinality columns :\nClaim_ID : 843, 563, 801, 957, 761, 621, 486, 571, 569\n/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n/\n \nCREATE TABLE \"Claims_Documents\" (\n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Created_by_Staff_ID\" INTEGER, \n\t\"Created_Date\" INTEGER, \n\tPRIMARY KEY (\"Claim_ID\", \"Document_Type_Code\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Created_by_Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Documents and all categories for low cardinality columns :\nClaim_ID : 69, 45, 90, 24, 82, 62, 39, 27, 81, 73\nDocument_Type_Code : Medical, Document, Photo\nCreated_by_Staff_ID : 427, 771, 986, 673, 687, 589, 735, 803, 718\nCreated_Date : 1, 2, 7, 8, 6, 3, 9\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 9590 Rogahn Point Apt. 466, 6830 Alexanne Forks Apt. 925, 319 Kozey Highway Suite 973\ncity : Edgardoberg, Gibsonfurt, Lake Floyd\nzip_postcode : 770, 116, 740\nstate_province_county : District of Columbia, Louisiana, SouthDakota\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n" }, { "role": "user", "content": "Find the ids and names of stations from which at least 200 trips started." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_id, start_station_name.\nThe SQL query I'll be generating is:\nSELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n/\n \nCREATE TABLE \"Reviewer\" (\n\t\"rID\" INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (\"rID\")\n)\n/\nColumns in Reviewer and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nname : Chris Jackson, Sarah Martinez, Mike Anderson, James Cameron, Elizabeth Thomas, Brittany Harris, Daniel Lewis, Ashley White\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"PROFESSOR\" (\n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"PROF_OFFICE\" VARCHAR(50), \n\t\"PROF_EXTENSION\" VARCHAR(4), \n\t\"PROF_HIGH_DEGREE\" VARCHAR(5), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/\nColumns in PROFESSOR and 3 examples in each column for high cardinality columns :\nEMP_NUM : 387, 301, 155\nDEPT_CODE : ECON/FIN, ART, HIST\nPROF_OFFICE : KLR 203E, BBG 208, AAK 230\nPROF_EXTENSION : 2248, 2851, 4436\n/\n/\nColumns in PROFESSOR and all categories for low cardinality columns :\nPROF_HIGH_DEGREE : Ph.D., MBA, MA, DBA\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n/\n \nCREATE TABLE school_bus (\n\t\"School_ID\" INTEGER, \n\t\"Driver_ID\" INTEGER, \n\t\"Years_Working\" INTEGER, \n\t\"If_full_time\" BOOLEAN, \n\tPRIMARY KEY (\"School_ID\", \"Driver_ID\"), \n\tFOREIGN KEY(\"Driver_ID\") REFERENCES driver (\"Driver_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_bus and all categories for low cardinality columns :\nSchool_ID : 1, 5, 7, 4, 3\nDriver_ID : 7, 4, 3, 10, 9\nYears_Working : 2, 8, 6, 3, 10\nIf_full_time : True\n/\n \nCREATE TABLE country (\n\t\"Country_id\" INTEGER, \n\t\"Country_name\" TEXT, \n\t\"Capital\" TEXT, \n\t\"Official_native_language\" TEXT, \n\tPRIMARY KEY (\"Country_id\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_id : 1, 2, 5, 4, 6, 3\nCountry_name : Isle of Man, Iran, United States, Indonesia, Iraq, Ireland\nCapital : Jakarta, Baghdad, Dublin, Tehran, Douglas, Washington\nOfficial_native_language : Arabic ( Arabic script ) Kurdish, English Manx, Persian ( Arabic script ), English, Bahasa Indonesia, Irish English\n/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n/\n \nCREATE TABLE \"Inst\" (\n\t\"instID\" INTEGER, \n\tname TEXT, \n\tcountry TEXT, \n\tPRIMARY KEY (\"instID\")\n)\n/\nColumns in Inst and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\nname : Northeastern University, INRIA, University of Oxford, Indiana University, Tohoku University, University of Pennsylvania, Portland State University, Google\ncountry : Japan, UK, USA, France\n/\n \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "What are the ids and names of all start stations that were the beginning of at least 200 trips?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_id, start_station_name.\nThe SQL query I'll be generating is:\nSELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n/\n \nCREATE TABLE event (\n\t\"Event_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\t\"Event_Attendance\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 4, 3\nDate : 9 April 2014, 7 October 2010, 11 October 2007, 13 October 2008, 20 June 2018\nVenue : Motagua, Platense, Hispano, Victoria, Marathon\nName : Global Awarding, Public Debating, Special Exhibition, Government Hearing, Olympia Games Openning\nEvent_Attendance : 369, 1675, 2356, 6650, 225\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE game (\n\tstadium_id INTEGER, \n\tid INTEGER, \n\t\"Season\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Home_team\" TEXT, \n\t\"Away_team\" TEXT, \n\t\"Score\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(stadium_id) REFERENCES stadium (id)\n)\n/\nColumns in game and 3 examples in each column for high cardinality columns :\nstadium_id : 1, 11, 2\nid : 17, 9, 16\nDate : 30 June 2013, 18 May 2007, 8 August 2009\nScore : 0–0 (7:6), –, 1–3\n/\n/\nColumns in game and all categories for low cardinality columns :\nSeason : 2009, 2013, 2008, 2012, 2011, 2010, 2007\nHome_team : Pakhtakor, Bunyodkor, Quruvchi\nAway_team : Pakhtakor, Bunyodkor, Quruvchi\nCompetition : League, Supercup, Cup\n/\n \nCREATE TABLE program (\n\t\"Program_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Origin\" TEXT, \n\t\"Launch\" REAL, \n\t\"Owner\" TEXT, \n\tPRIMARY KEY (\"Program_ID\")\n)\n/\nColumns in program and all categories for low cardinality columns :\nProgram_ID : 1, 2, 5, 4, 3\nName : Toonmax, Aniworld, Youman, Jiajia, Kaku\nOrigin : Beijing, Shanghai, Guangdong, Hunan, Jiangsu\nLaunch : 2007.0, 2005.0, 2010.0, 2004.0\nOwner : Jiangsu Broadcasting Corporation (JSBC), Shanghai Media Group (SMG), Beijing Television (BTV), Hunan Broadcasting System (HBS), Southern Media Corporation (SMC)\n/\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n/\n/\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n/\n" }, { "role": "user", "content": "Find the zip code in which the average mean visibility is lower than 10." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_visibility_miles.\nThe SQL query I'll be generating is:\nSELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Product_Categories\" (\n\tproduction_type_code VARCHAR(15), \n\tproduct_type_description VARCHAR(80), \n\tvat_rating DECIMAL(19, 4), \n\tPRIMARY KEY (production_type_code)\n)\n/\nColumns in Product_Categories and all categories for low cardinality columns :\nproduction_type_code : Food, Books, DVDs, Electronics\nproduct_type_description : Food, Books, Dvd products, Electrical devices\nvat_rating : 15.8400, 11.4000, 13.9500, 17.9000\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n/\n/\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n/\n \nCREATE TABLE college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE hosting_city (\n\t\"Year\" INTEGER, \n\t\"Match_ID\" INTEGER, \n\t\"Host_City\" TEXT, \n\tPRIMARY KEY (\"Year\"), \n\tFOREIGN KEY(\"Match_ID\") REFERENCES \"match\" (\"Match_ID\"), \n\tFOREIGN KEY(\"Host_City\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in hosting_city and all categories for low cardinality columns :\nYear : 2009, 2013, 2012, 2008, 2011, 2010\nMatch_ID : 1, 2, 5, 4, 6, 3\nHost_City : 1, 11, 2, 6, 12\n/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"CLASS\" (\n\t\"CLASS_CODE\" VARCHAR(5), \n\t\"CRS_CODE\" VARCHAR(10), \n\t\"CLASS_SECTION\" VARCHAR(2), \n\t\"CLASS_TIME\" VARCHAR(20), \n\t\"CLASS_ROOM\" VARCHAR(8), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"CLASS_CODE\"), \n\tFOREIGN KEY(\"CRS_CODE\") REFERENCES \"COURSE\" (\"CRS_CODE\"), \n\tFOREIGN KEY(\"PROF_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/\nColumns in CLASS and 3 examples in each column for high cardinality columns :\nCLASS_CODE : 10013, 10024, 10016\n/\n/\nColumns in CLASS and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nCLASS_SECTION : 1, 2, 3\nCLASS_TIME : TTh 2:30-3:45 p.m., MWF 10:00-10:50 a.m., MWF 9:00-9:50 a.m., MWF 8:00-8:50 a.m., W 6:00-8:40 p.m., Th 6:00-8:40 p.m., TTh 1:00-2:15 p.m., MWF 11:00-11:50 a.m.\nCLASS_ROOM : KLR209, KLR211, BUS252, BUS311, KLR200, BUS200\nPROF_NUM : 114, 342, 301, 228, 105, 162\n/\n \nCREATE TABLE \"Companies\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value_billion\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Companies and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : PetroChina, Berkshire Hathaway, Petrobras\nSales_billion : 69.2, 189.6, 421.8\nProfits_billion : 16.4, 19.9, 17.4\nAssets_billion : 2467.9, 192.8, 1913.9\nMarket_Value_billion : 239.5, 186.5, 224.8\n/\n/\nColumns in Companies and all categories for low cardinality columns :\nHeadquarters : Spain, UK, China, Brazil, France, Russia, USA, Netherlands\nIndustry : Retailing, Conglomerate, Oil and gas, Telecommunications, Banking\n/\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n/\n \nCREATE TABLE branch (\n\t\"Branch_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Open_year\" TEXT, \n\t\"Address_road\" TEXT, \n\t\"City\" TEXT, \n\tmembership_amount TEXT, \n\tPRIMARY KEY (\"Branch_ID\")\n)\n/\nColumns in branch and all categories for low cardinality columns :\nBranch_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Popert, Zytogorski, Alexandre, Brooke Greville, Taverner, Stanley, Saint Amant, Cochrane\nOpen_year : 2009, 2013, 2015, 2001, 2012, 2014\nAddress_road : Abbott Street, Concord Road, Brampton Road, Cecilia Avenue, Oaks Crescent, Valleys Place, Glebe Street, Abbey Rise\nCity : Oxford, London\nmembership_amount : 91, 56, 11, 1418, 7, 6, 112, 31\n/\n" }, { "role": "user", "content": "For each zip code, select all those that have an average mean visiblity below 10." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, mean_visibility_miles.\nThe SQL query I'll be generating is:\nSELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Attribute_Definitions\" (\n\tattribute_id INTEGER, \n\tattribute_name VARCHAR(30), \n\tattribute_data_type VARCHAR(10), \n\tPRIMARY KEY (attribute_id)\n)\n/\nColumns in Attribute_Definitions and all categories for low cardinality columns :\nattribute_id : 1, 2, 4, 3\nattribute_name : Yellow, Sweet, Green, Black\nattribute_data_type : Bool\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Parking_Fines\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Parking_Fines and all categories for low cardinality columns :\ncouncil_tax_id : 10, 9\ncmi_cross_ref_id : 4, 81\n/\n \nCREATE TABLE \"School\" (\n\t\"School_id\" TEXT, \n\t\"School_name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Mascot\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"IHSAA_Class\" TEXT, \n\t\"IHSAA_Football_Class\" TEXT, \n\t\"County\" TEXT, \n\tPRIMARY KEY (\"School_id\")\n)\n/\nColumns in School and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\nSchool_name : New Prairie 1, Triton, LaVille, Glenn, Culver Community, Jimtown, Knox Community, Bremen\nLocation : Bourbon, Walkerton, Lakeville, Knox, Culver, New Carlisle, Elkhart, Bremen\nMascot : Lancers, Cougars, Cavaliers, Trojans, Redskins, Falcons, Lions, Jimmies\nEnrollment : 601, 605, 287, 495, 620, 379, 852, 316\nIHSAA_Class : AA, A, AAA\nIHSAA_Football_Class : AA, A, AAA, AAAA\nCounty : 20 Elkhart, 50 Marshall, 75 Starke, 71 St. Joseph, 46 LaPorte 71 St. Joseph\n/\n \nCREATE TABLE film_text (\n\tfilm_id SMALLINT NOT NULL, \n\ttitle VARCHAR(255) NOT NULL, \n\tdescription TEXT, \n\tPRIMARY KEY (film_id)\n)\n/\nColumns in film_text and all categories for low cardinality columns :\nfilm_id : \ntitle : \ndescription : \n/\n \nCREATE TABLE captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\n/\n \nCREATE TABLE \"Documents\" (\n\tdocument_code VARCHAR(15), \n\tdocument_structure_code VARCHAR(15) NOT NULL, \n\tdocument_type_code VARCHAR(15) NOT NULL, \n\taccess_count INTEGER, \n\tdocument_name VARCHAR(80), \n\tPRIMARY KEY (document_code), \n\tFOREIGN KEY(document_structure_code) REFERENCES \"Document_Structures\" (document_structure_code)\n)\n/\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_code : 510, 714, 217\naccess_count : 8208, 3289, 2294\ndocument_name : Learning English, Summer Sails, Learning Database\n/\n/\nColumns in Documents and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\ndocument_type_code : Book, Advertisement, CV, Paper\n/\n \nCREATE TABLE mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\n/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Customer_Orders\" (\n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Store_ID\" INTEGER NOT NULL, \n\t\"Order_Date\" DATETIME NOT NULL, \n\t\"Planned_Delivery_Date\" DATETIME NOT NULL, \n\t\"Actual_Delivery_Date\" DATETIME NOT NULL, \n\t\"Other_Order_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Order_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\"), \n\tFOREIGN KEY(\"Store_ID\") REFERENCES \"Stores\" (\"Store_ID\"), \n\tUNIQUE (\"Order_ID\")\n)\n/\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\nOrder_ID : 1, 13, 11\nOrder_Date : 2000-07-03 21:41:50, 2003-06-24 11:44:51, 1998-03-10 14:01:00\nPlanned_Delivery_Date : 2012-05-19 00:38:52, 1990-09-25 07:14:01, 2004-04-24 01:52:57\nActual_Delivery_Date : 2003-12-16 23:37:19, 1998-08-22 17:57:32, 1993-09-16 23:20:05\n/\n/\nColumns in Customer_Orders and all categories for low cardinality columns :\nCustomer_ID : 556, 240, 712, 304, 546, 516, 418\nStore_ID : 518, 150, 229, 291, 444, 231, 512, 421, 344\nOther_Order_Details : None\n/\n \nCREATE TABLE \"People\" (\n\tperson_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(255), \n\tmiddle_name VARCHAR(255), \n\tlast_name VARCHAR(255), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (person_id)\n)\n/\nColumns in People and all categories for low cardinality columns :\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\nfirst_name : Shannon, Mayra, Hoyt, Virginie, Nova, Dariana, Verna, Lizeth\nmiddle_name : Arielle, Jasmin, Haley, Amiya, Mercedes, Bell, Elissa, Hayley\nlast_name : Hartmann, Senger, Bednar, Wintheiser, Feest, Grant, Bartoletti\ncell_mobile_number : 1-603-110-0647, (508)319-2970x043, 724-681-4161x51632, 1-372-548-7538x314, (262)347-9364x516, 812.228.0645x91481, 01955267735, 766-272-9964\nemail_address : stanley.monahan@example.org, adele.gibson@example.net, terry.kuhlman@example.org, boyer.lonie@example.com, celestine11@example.net, oreynolds@example.com, javier.trantow@example.net, leila14@example.net\nlogin_name : uuol, mkou, qrwl, bkkv, pgub, bnto, zops, rzxu\npassword : ecae473cb54601e01457078ac0cdf4a1ced837bb, b063331ea8116befaa7b84c59c6a22200f5f8caa, 5e4ff49a61b3544da3ad7dc7e2cf28847564c64c, 7be9c03d5467d563555c51ebb3eb78e7f90832ec, 7dce9b688636ee212294c257dd2f6b85c7f65f2e, 76a93d1d3b7becc932d203beac61d064bd54e947, c55795df86182959094b83e27900f7cf44ced570, b20b6a9f24aadeda70d54e410c3219f61fb063fb\n/\n" }, { "role": "user", "content": "List all the cities in a decreasing order of each city's stations' highest latitude." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, lat.\nThe SQL query I'll be generating is:\nSELECT city FROM station GROUP BY city ORDER BY max(lat) DESC" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE device (\n\t\"Device_ID\" INTEGER, \n\t\"Device\" TEXT, \n\t\"Carrier\" TEXT, \n\t\"Package_Version\" TEXT, \n\t\"Applications\" TEXT, \n\t\"Software_Platform\" TEXT, \n\tPRIMARY KEY (\"Device_ID\")\n)\n/\nColumns in device and all categories for low cardinality columns :\nDevice_ID : 1, 2, 5, 4, 6, 3\nDevice : Huawei, Galaxy, Apple, Xiaomi, BlackBerry Storm 9530, Samsung\nCarrier : MTS Mobility, Bell Mobility, Telus Mobility, Vodafone AU, Verizon Wireless, Iusacell\nPackage_Version : 4.7.0.208, 5.0.0.742, 5.0.0.808, 5.0.0.328, 5.0.0.419\nApplications : 4.7.0.151, 5.0.0.451, 5.0.0.328, 5.0.0.419\nSoftware_Platform : iOS, Android\n/\n \nCREATE TABLE event (\n\t\"Event_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\t\"Event_Attendance\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 4, 3\nDate : 9 April 2014, 7 October 2010, 11 October 2007, 13 October 2008, 20 June 2018\nVenue : Motagua, Platense, Hispano, Victoria, Marathon\nName : Global Awarding, Public Debating, Special Exhibition, Government Hearing, Olympia Games Openning\nEvent_Attendance : 369, 1675, 2356, 6650, 225\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n/\n/\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n/\n \nCREATE TABLE \"Tasks\" (\n\ttask_id INTEGER, \n\tproject_id INTEGER NOT NULL, \n\ttask_details VARCHAR(255) NOT NULL, \n\t\"eg Agree Objectives\" VARCHAR(1), \n\tPRIMARY KEY (task_id), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/\nColumns in Tasks and 3 examples in each column for high cardinality columns :\ntask_id : 1, 13, 11\nproject_id : 1, 13, 11\ntask_details : t, m, q\n/\n/\nColumns in Tasks and all categories for low cardinality columns :\neg Agree Objectives : None\n/\n \nCREATE TABLE school_details (\n\t\"School_ID\" INTEGER, \n\t\"Nickname\" TEXT, \n\t\"Colors\" TEXT, \n\t\"League\" TEXT, \n\t\"Class\" TEXT, \n\t\"Division\" TEXT, \n\tPRIMARY KEY (\"School_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_details and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nNickname : Auks, Raiders, Silver Eagles, Seahawks, Buccaneers, Tigers\nColors : Dark Green and White, Blue and Yellow, Maroon and White, Blue and Gold, Garnet and White, Silver and Maroon\nLeague : DSHA\nClass : Flight B, Flight A, Fight A\nDivision : Division 1, Division 2, Division 3\n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"STUDENT\" (\n\t\"STU_NUM\" INTEGER, \n\t\"STU_LNAME\" VARCHAR(15), \n\t\"STU_FNAME\" VARCHAR(15), \n\t\"STU_INIT\" VARCHAR(1), \n\t\"STU_DOB\" DATETIME, \n\t\"STU_HRS\" INTEGER, \n\t\"STU_CLASS\" VARCHAR(2), \n\t\"STU_GPA\" FLOAT, \n\t\"STU_TRANSFER\" NUMERIC, \n\t\"DEPT_CODE\" VARCHAR(18), \n\t\"STU_PHONE\" VARCHAR(4), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"STU_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n) \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n/\n \nCREATE TABLE \"Member_of\" (\n\t\"FacID\" INTEGER, \n\t\"DNO\" INTEGER, \n\t\"Appt_Type\" VARCHAR(15), \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Member_of and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\n/\n/\nColumns in Member_of and all categories for low cardinality columns :\nDNO : 50, 550, 520, 600\nAppt_Type : Secondary, Primary\n/\n \nCREATE TABLE departments (\n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT '0' NOT NULL, \n\t\"DEPARTMENT_NAME\" VARCHAR(30) NOT NULL, \n\t\"MANAGER_ID\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"LOCATION_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"DEPARTMENT_ID\")\n)\n/\nColumns in departments and 3 examples in each column for high cardinality columns :\nDEPARTMENT_ID : 170, 160, 120\nDEPARTMENT_NAME : Shipping, Purchasing, Corporate Tax\nMANAGER_ID : 114, 201, 108\n/\n/\nColumns in departments and all categories for low cardinality columns :\nLOCATION_ID : 1700, 1800, 2700, 2400, 2500, 1500, 1400\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE phone (\n\t\"Name\" TEXT, \n\t\"Phone_ID\" INTEGER, \n\t\"Memory_in_G\" INTEGER, \n\t\"Carrier\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Phone_ID\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nName : IPhone 6s, IPhone 7, IPhone X, IPhone 6, IPhone 5s\nPhone_ID : 1, 2, 5, 4, 3\nMemory_in_G : 128, 32, 16, 64\nCarrier : Sprint, TMobile\nPrice : 320.0, 1000.0, 480.0, 899.0, 699.0\n/\n" }, { "role": "user", "content": "For each city, list their names in decreasing order by their highest station latitude." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station.\nFrom these tables, I'll be using the following columns: city, lat.\nThe SQL query I'll be generating is:\nSELECT city FROM station GROUP BY city ORDER BY max(lat) DESC" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n/\n \nCREATE TABLE \"Patient\" (\n\t\"SSN\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Address\" VARCHAR(30) NOT NULL, \n\t\"Phone\" VARCHAR(30) NOT NULL, \n\t\"InsuranceID\" INTEGER NOT NULL, \n\t\"PCP\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"SSN\"), \n\tCONSTRAINT \"fk_Patient_Physician_EmployeeID\" FOREIGN KEY(\"PCP\") REFERENCES \"Physician\" (\"EmployeeID\")\n)\n/\nColumns in Patient and all categories for low cardinality columns :\nSSN : 100000001, 100000002, 100000004, 100000003\nName : Grace Ritchie, Random J. Patient, John Smith, Dennis Doe\nAddress : 1100 Foobaz Avenue, 101 Omgbbq Street, 42 Foobar Lane, 37 Snafu Drive\nPhone : 555-1204, 555-0512, 555-0256, 555-2048\nInsuranceID : 68421879, 65465421, 36546321, 68476213\nPCP : 1, 2, 3\n/\n \nCREATE TABLE repair_assignment (\n\ttechnician_id INTEGER, \n\t\"repair_ID\" INTEGER, \n\t\"Machine_ID\" INTEGER, \n\tPRIMARY KEY (technician_id, \"repair_ID\", \"Machine_ID\"), \n\tFOREIGN KEY(\"Machine_ID\") REFERENCES machine (\"Machine_ID\"), \n\tFOREIGN KEY(\"repair_ID\") REFERENCES repair (\"repair_ID\"), \n\tFOREIGN KEY(technician_id) REFERENCES technician (technician_id)\n)\n/\nColumns in repair_assignment and all categories for low cardinality columns :\ntechnician_id : 1, 2, 5, 7, 3\nrepair_ID : 1, 2, 5, 8, 4, 3\nMachine_ID : 1, 2, 7, 4, 6, 3\n/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n \nCREATE TABLE weekly_weather (\n\tstation_id INTEGER, \n\tday_of_week TEXT, \n\thigh_temperature INTEGER, \n\tlow_temperature INTEGER, \n\tprecipitation REAL, \n\twind_speed_mph INTEGER, \n\tPRIMARY KEY (station_id, day_of_week), \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in weekly_weather and 3 examples in each column for high cardinality columns :\nwind_speed_mph : 13, 20, 7\n/\n/\nColumns in weekly_weather and all categories for low cardinality columns :\nstation_id : 1, 2, 4, 3, 10\nday_of_week : Sunday, Wednesday, Tuesday, Thursday, Monday, Friday, Saturday\nhigh_temperature : 55, 49, 58, 50, 66, 59, 60, 57, 54\nlow_temperature : 56, 46, 55, 49, 50, 52, 54\nprecipitation : 60.0, 30.0, 10.0, 90.0, 50.0, 70.0, 80.0, 20.0\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE match_result (\n\t\"Rank\" INTEGER, \n\t\"Club_ID\" INTEGER, \n\t\"Gold\" INTEGER, \n\t\"Big_Silver\" INTEGER, \n\t\"Small_Silver\" INTEGER, \n\t\"Bronze\" INTEGER, \n\t\"Points\" INTEGER, \n\tPRIMARY KEY (\"Rank\", \"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in match_result and all categories for low cardinality columns :\nRank : 1, 2, 5, 4, 6, 3\nClub_ID : 1, 2, 5, 4, 6, 3\nGold : 13, 20, 5, 7, 6, 12\nBig_Silver : 11, 7, 6, 12, 14, 9\nSmall_Silver : 16, 4, 6, 10, 9\nBronze : 7, 8, 6, 10, 9\nPoints : 89, 102, 84, 66, 139, 168\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n" }, { "role": "user", "content": "What are the dates that had the top 5 cloud cover rates? Also tell me the cloud cover rate." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, cloud_cover.\nThe SQL query I'll be generating is:\nSELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n/\n \nCREATE TABLE \"Documents_with_Expenses\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Budget_Type_Code\") REFERENCES \"Ref_Budget_Codes\" (\"Budget_Type_Code\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Documents_with_Expenses and all categories for low cardinality columns :\nDocument_ID : 300, 240, 309, 226, 367, 371, 383, 227, 192, 57\nBudget_Type_Code : GV, SF, ORG\nDocument_Details : government, safety, organization\n/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n/\n \nCREATE TABLE \"Employee\" (\n\t\"EmployeeId\" INTEGER NOT NULL, \n\t\"LastName\" VARCHAR(20) NOT NULL, \n\t\"FirstName\" VARCHAR(20) NOT NULL, \n\t\"Title\" VARCHAR(30) DEFAULT NULL, \n\t\"ReportsTo\" INTEGER DEFAULT NULL, \n\t\"BirthDate\" DATETIME DEFAULT NULL, \n\t\"HireDate\" DATETIME DEFAULT NULL, \n\t\"Address\" VARCHAR(70) DEFAULT NULL, \n\t\"City\" VARCHAR(40) DEFAULT NULL, \n\t\"State\" VARCHAR(40) DEFAULT NULL, \n\t\"Country\" VARCHAR(40) DEFAULT NULL, \n\t\"PostalCode\" VARCHAR(10) DEFAULT NULL, \n\t\"Phone\" VARCHAR(24) DEFAULT NULL, \n\t\"Fax\" VARCHAR(24) DEFAULT NULL, \n\t\"Email\" VARCHAR(60) DEFAULT NULL, \n\tPRIMARY KEY (\"EmployeeId\"), \n\tFOREIGN KEY(\"ReportsTo\") REFERENCES \"Employee\" (\"EmployeeId\")\n)\n/\nColumns in Employee and all categories for low cardinality columns :\nEmployeeId : 1, 2, 5, 7, 8, 4, 6, 3\nLastName : Callahan, Mitchell, Adams, Park, Edwards, Peacock, Johnson, King\nFirstName : Jane, Michael, Steve, Laura, Margaret, Andrew, Robert, Nancy\nTitle : IT Staff, Sales Manager, IT Manager, Sales Support Agent, General Manager\nReportsTo : 1, None, 2, 6\nBirthDate : 1973-07-01 00:00:00, 1962-02-18 00:00:00, 1968-01-09 00:00:00, 1947-09-19 00:00:00, 1973-08-29 00:00:00, 1965-03-03 00:00:00, 1970-05-29 00:00:00, 1958-12-08 00:00:00\nHireDate : 2002-04-01 00:00:00, 2003-10-17 00:00:00, 2002-05-01 00:00:00, 2004-01-02 00:00:00, 2003-05-03 00:00:00, 2002-08-14 00:00:00, 2004-03-04 00:00:00\nAddress : 11120 Jasper Ave NW, 1111 6 Ave SW, 683 10 Street SW, 7727B 41 Ave, 590 Columbia Boulevard West, 923 7 ST NW, 825 8 Ave SW, 5827 Bowness Road NW\nCity : Edmonton, Calgary, Lethbridge\nState : AB\nCountry : Canada\nPostalCode : T1K 5N8, T3B 0C5, T5K 2N1, T2P 5G3, T2P 5M5, T3B 1Y7, T1H 1Y8, T2P 2T3\nPhone : +1 (403) 262-3443, 1 (780) 836-9987, +1 (403) 246-9887, +1 (780) 428-9482, +1 (403) 456-9986, +1 (403) 467-3351, +1 (403) 263-4423\nFax : +1 (403) 467-8772, +1 (403) 262-3322, +1 (403) 456-8485, +1 (403) 246-9899, +1 (403) 262-6712, +1 (403) 263-4289, +1 (780) 428-3457, 1 (780) 836-9543\nEmail : robert@chinookcorp.com, jane@chinookcorp.com, margaret@chinookcorp.com, steve@chinookcorp.com, michael@chinookcorp.com, andrew@chinookcorp.com, nancy@chinookcorp.com, laura@chinookcorp.com\n/\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n/\n/\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n/\n\n \nCREATE TABLE \"League\" (\n\tid INTEGER, \n\tcountry_id INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(country_id) REFERENCES \"Country\" (id)\n)\n/\nColumns in League and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\ncountry_id : 1, 19694, 7809\nname : Portugal Liga ZON Sagres, England Premier League, Belgium Jupiler League\n/\n\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n" }, { "role": "user", "content": "What are the dates that have the 5 highest cloud cover rates and what are the rates?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: date, cloud_cover.\nThe SQL query I'll be generating is:\nSELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Organizations\" (\n\torganization_id INTEGER NOT NULL, \n\tparent_organization_id INTEGER, \n\torganization_details VARCHAR(255), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 7, 8, 10\nparent_organization_id : 7, 8\norganization_details : Denesik and Sons Party, Reinger, Hudson and Nolan Group, Robel-Schulist Group\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE roller_coaster (\n\t\"Roller_Coaster_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Park\" TEXT, \n\t\"Country_ID\" INTEGER, \n\t\"Length\" REAL, \n\t\"Height\" REAL, \n\t\"Speed\" TEXT, \n\t\"Opened\" TEXT, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (\"Roller_Coaster_ID\"), \n\tFOREIGN KEY(\"Country_ID\") REFERENCES country (\"Country_ID\")\n)\n/\nColumns in roller_coaster and all categories for low cardinality columns :\nRoller_Coaster_ID : 1, 2, 5, 4, 6, 3\nName : The Voyage, Twister, Boardwalk Bullet, Hades 360, Dauling Dragon, Ravine Flyer II\nPark : Waldameer, Happy Valley, Mt. Olympus, Gröna Lund, Kemah Boardwalk, Holiday World\nCountry_ID : 1, 2, 3\nLength : 6442.0, 4726.0, 3236.0, 1574.0, 2900.0, 3914.0\nHeight : 96.0, 105.0, 136.0, 50.0, 120.0, 163.0\nSpeed : 67, 55, 37.9, 70, 57, 51\nOpened : May 14, 2005, 2012, August 31, 2007, 2011, May 6, 2006, May 17, 2008\nStatus : Operating\n/\n \nCREATE TABLE \"Student_Course_Enrolment\" (\n\tregistration_id INTEGER, \n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_enrolment DATETIME NOT NULL, \n\tdate_of_completion DATETIME NOT NULL, \n\tPRIMARY KEY (registration_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/\nColumns in Student_Course_Enrolment and 3 examples in each column for high cardinality columns :\nregistration_id : 17, 9, 16\nstudent_id : 3, 13, 11\ndate_of_enrolment : 2017-12-16 15:53:06, 2017-10-10 10:05:03, 2017-12-07 02:21:13\ndate_of_completion : 2018-03-01 07:12:39, 2018-03-22 18:04:54, 2018-03-07 09:45:48\n/\n/\nColumns in Student_Course_Enrolment and all categories for low cardinality columns :\ncourse_id : 1, 11, 2, 15, 7, 8, 4, 14, 10, 9\n/\n \nCREATE TABLE event (\n\t\"ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Stadium_ID\" INTEGER, \n\t\"Year\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Stadium_ID\") REFERENCES stadium (\"ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nID : 1, 2, 5, 4, 6, 3\nName : Pacific, European FINA, FINA, World Master, IPC, World Junior\nStadium_ID : 1, 2, 8, 4, 3, 10\nYear : 2016, 2013, 2012, 2017, 2011, 2014\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Track\" (\n\t\"TrackId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(200) NOT NULL, \n\t\"AlbumId\" INTEGER DEFAULT NULL, \n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"GenreId\" INTEGER DEFAULT NULL, \n\t\"Composer\" VARCHAR(220) DEFAULT NULL, \n\t\"Milliseconds\" INTEGER NOT NULL, \n\t\"Bytes\" INTEGER DEFAULT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"TrackId\"), \n\tFOREIGN KEY(\"MediaTypeId\") REFERENCES \"MediaType\" (\"MediaTypeId\"), \n\tFOREIGN KEY(\"GenreId\") REFERENCES \"Genre\" (\"GenreId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Album\" (\"AlbumId\")\n)\n/\nColumns in Track and 3 examples in each column for high cardinality columns :\nTrackId : 87, 56, 65\nName : Snoopy's search-Red baron, The Winner Loses, Leave My Girl Alone\nAlbumId : 17, 9, 16\nComposer : Ned Fairchild, Tony Iommi, Bill Ward, Geezer Butler, Ozzy Osbourne, Berry Gordy, Jr./Janie Bradford\nMilliseconds : 263497, 307617, 204721\nBytes : 6859518, 2301989, 6420530\n/\n/\nColumns in Track and all categories for low cardinality columns :\nMediaTypeId : 1, 2\nGenreId : 1, 2, 5, 4, 6, 3\nUnitPrice : 0.99\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n/\n \nCREATE TABLE \"Projects\" (\n\tproject_id INTEGER, \n\torganisation_id INTEGER NOT NULL, \n\tproject_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (project_id), \n\tFOREIGN KEY(organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/\nColumns in Projects and 3 examples in each column for high cardinality columns :\nproject_id : 1, 13, 11\nproject_details : doloremque, impedit, et\n/\n/\nColumns in Projects and all categories for low cardinality columns :\norganisation_id : 1, 13, 11, 10, 5, 7, 4, 12, 3, 15\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n/\n/\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n/\n \nCREATE TABLE machine (\n\t\"Machine_ID\" INTEGER, \n\t\"Making_Year\" INTEGER, \n\t\"Class\" TEXT, \n\t\"Team\" TEXT, \n\t\"Machine_series\" TEXT, \n\tvalue_points REAL, \n\tquality_rank INTEGER, \n\tPRIMARY KEY (\"Machine_ID\")\n)\n/\nColumns in machine and all categories for low cardinality columns :\nMachine_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMaking_Year : 1992, 1993, 1994, 1999, 1991, 1996, 1997, 1998, 1995\nClass : 125cc\nTeam : Honda, Team Givi- Honda LCR, Givi Racing- Honda, Marlboro Pileri - Honda, Hero Sports TS- Honda\nMachine_series : RS125\nvalue_points : 238.0, 105.0, 171.0, 129.0, 57.0, 62.0, 126.0, 194.0, 65.0\nquality_rank : 1, 13, 11, 2, 5, 7, 8, 4, 3\n/\n \nCREATE TABLE \"Restaurant_Type\" (\n\t\"ResTypeID\" INTEGER, \n\t\"ResTypeName\" VARCHAR(40), \n\t\"ResTypeDescription\" VARCHAR(100), \n\tPRIMARY KEY (\"ResTypeID\")\n)\n/\nColumns in Restaurant_Type and all categories for low cardinality columns :\nResTypeID : 1, 2\nResTypeName : Sandwich, Stir-fry\nResTypeDescription : Classic Chinese cooking., Simplest there is.\n/\n \nCREATE TABLE hosting_city (\n\t\"Year\" INTEGER, \n\t\"Match_ID\" INTEGER, \n\t\"Host_City\" TEXT, \n\tPRIMARY KEY (\"Year\"), \n\tFOREIGN KEY(\"Match_ID\") REFERENCES \"match\" (\"Match_ID\"), \n\tFOREIGN KEY(\"Host_City\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in hosting_city and all categories for low cardinality columns :\nYear : 2009, 2013, 2012, 2008, 2011, 2010\nMatch_ID : 1, 2, 5, 4, 6, 3\nHost_City : 1, 11, 2, 6, 12\n/\n" }, { "role": "user", "content": "What are the ids and durations of the trips with the top 3 durations?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration.\nThe SQL query I'll be generating is:\nSELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n/\n \nCREATE TABLE \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\n/\n \nCREATE TABLE protein (\n\tcommon_name TEXT, \n\tprotein_name TEXT, \n\tdivergence_from_human_lineage REAL, \n\taccession_number TEXT, \n\tsequence_length REAL, \n\tsequence_identity_to_human_protein TEXT, \n\t\"Institution_id\" TEXT, \n\tPRIMARY KEY (common_name), \n\tFOREIGN KEY(\"Institution_id\") REFERENCES \"Institution\" (\"Institution_id\")\n)\n/\nColumns in protein and all categories for low cardinality columns :\ncommon_name : Tropical Clawed Frog, porkworm, body louse, southern house mosquito, purple sea urchin\nprotein_name : uncharacterized protein LOC578090, conserved hypothetical protein, Centromeric protein E, putative, surface antigen repeat family protein, uncharacterized protein C20orf117-like\ndivergence_from_human_lineage : 937.5, 742.9, 782.7, 371.2\naccession_number : XP_003380263.1, XP_002942331.1, XP_783370.2, XP_002429877.1, XP_001843754.1\nsequence_length : 2030.0, 1587.0, 2086.0, 1584.0, 1878.0\nsequence_identity_to_human_protein : 30%, 47%, 36%, 39%, 32%\nInstitution_id : 1, 5, 9, 3\n/\n \nCREATE TABLE \"Research_Staff\" (\n\tstaff_id INTEGER, \n\temployer_organisation_id INTEGER NOT NULL, \n\tstaff_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(employer_organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/\nColumns in Research_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_details : aspernatur, dicta, ab\n/\n/\nColumns in Research_Staff and all categories for low cardinality columns :\nemployer_organisation_id : 1, 2, 5, 8, 4, 6, 3, 10, 9\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n/\n/\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n/\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE enrollments (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"TotalEnrollment_AY\" INTEGER, \n\t\"FTE_AY\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Year\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in enrollments and 3 examples in each column for high cardinality columns :\nYear : 1979, 2004, 1937\nTotalEnrollment_AY : 495, 5734, 9547\nFTE_AY : 3877, 14324, 12876\n/\n/\nColumns in enrollments and all categories for low cardinality columns :\nCampus : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE \"Vocals\" (\n\t\"SongId\" INTEGER, \n\t\"Bandmate\" INTEGER, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"Bandmate\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"Bandmate\") REFERENCES \"Band\" (\"Id\")\n)\n/\nColumns in Vocals and all categories for low cardinality columns :\nSongId : \nBandmate : \nType : \n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n/\n \nCREATE TABLE party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\n/\n" }, { "role": "user", "content": "What are the ids of the trips that lasted the longest and how long did they last?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration.\nThe SQL query I'll be generating is:\nSELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n/\n\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"COURSE\" (\n\t\"CRS_CODE\" VARCHAR(10), \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"CRS_DESCRIPTION\" VARCHAR(35), \n\t\"CRS_CREDIT\" FLOAT, \n\tPRIMARY KEY (\"CRS_CODE\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/\nColumns in COURSE and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nDEPT_CODE : CIS, ACCT\nCRS_DESCRIPTION : Statistical Applications, Accounting I, Accounting II, Database Design and Implementation, Intro. to Microcomputing, Intro. to Statistics\nCRS_CREDIT : 3.0, 4.0\n/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n/\n \nCREATE TABLE pilot_record (\n\t\"Record_ID\" INTEGER, \n\t\"Pilot_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\t\"Date\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\", \"Aircraft_ID\", \"Date\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Pilot_ID\") REFERENCES pilot (\"Pilot_ID\")\n)\n/\nColumns in pilot_record and all categories for low cardinality columns :\nRecord_ID : 1, 2, 5, 4, 6, 3\nPilot_ID : 1, 2, 4, 3\nAircraft_ID : 1, 2, 5, 4, 6\nDate : 2006/01/04, 2005/01/04, 2008/01/04, 2004/01/04, 2007/01/04, 2003/01/04\n/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n/\n/\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n \nCREATE TABLE \"Museums\" (\n\t\"Museum_ID\" INTEGER NOT NULL, \n\t\"Museum_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Museum_ID\"), \n\tFOREIGN KEY(\"Museum_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Museums and all categories for low cardinality columns :\nMuseum_ID : 2113, 2701, 5076\nMuseum_Details : MoMA, The Metropolitan Museum of Art, Yale Center for British Art\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n" }, { "role": "user", "content": "For each station, return its longitude and the average duration of trips that started from the station." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.name, station.long, trip.duration, station.id, trip.start_station_id.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Mailshot_Campaigns\" (\n\tmailshot_id INTEGER, \n\tproduct_category VARCHAR(15), \n\tmailshot_name VARCHAR(80), \n\tmailshot_start_date DATETIME, \n\tmailshot_end_date DATETIME, \n\tPRIMARY KEY (mailshot_id)\n)\n/\nColumns in Mailshot_Campaigns and 3 examples in each column for high cardinality columns :\nmailshot_id : 17, 9, 16\nmailshot_start_date : 2017-05-20 20:05:09, 2018-02-04 13:13:36, 2017-09-27 02:35:45\nmailshot_end_date : 2018-03-15 01:06:16, 2018-03-13 14:42:26, 2018-03-01 13:42:09\n/\n/\nColumns in Mailshot_Campaigns and all categories for low cardinality columns :\nproduct_category : food, clothes\nmailshot_name : USPS, US, AL, FED\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n/\n \nCREATE TABLE \"Ref_Product_Categories\" (\n\tproduct_category_code VARCHAR(15), \n\tproduct_category_description VARCHAR(80), \n\tunit_of_measure VARCHAR(20), \n\tPRIMARY KEY (product_category_code)\n)\n/\nColumns in Ref_Product_Categories and all categories for low cardinality columns :\nproduct_category_code : Spices, Seeds, Herbs\nproduct_category_description : Spices, Seeds, Herbs\nunit_of_measure : Weight - pound,kilo., Handful \n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Department_Store_Chain\" (\n\tdept_store_chain_id INTEGER, \n\tdept_store_chain_name VARCHAR(80), \n\tPRIMARY KEY (dept_store_chain_id)\n)\n/\nColumns in Department_Store_Chain and all categories for low cardinality columns :\ndept_store_chain_id : 1, 2, 4, 3\ndept_store_chain_name : West, East, North, South\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n/\n \nCREATE TABLE \"Staff\" (\n\t\"Staff_ID\" INTEGER NOT NULL, \n\t\"Staff_Details\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Staff_ID\")\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nStaff_ID : 510, 427, 771\nStaff_Details : Gideon, Vernie, Roman\n/\n\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE country (\n\t\"Country_id\" INTEGER, \n\t\"Country_name\" TEXT, \n\t\"Capital\" TEXT, \n\t\"Official_native_language\" TEXT, \n\tPRIMARY KEY (\"Country_id\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_id : 1, 2, 5, 4, 6, 3\nCountry_name : Isle of Man, Iran, United States, Indonesia, Iraq, Ireland\nCapital : Jakarta, Baghdad, Dublin, Tehran, Douglas, Washington\nOfficial_native_language : Arabic ( Arabic script ) Kurdish, English Manx, Persian ( Arabic script ), English, Bahasa Indonesia, Irish English\n/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n/\n \nCREATE TABLE \"Statements\" (\n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Statement_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Statement_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Statements and all categories for low cardinality columns :\nStatement_ID : 192, 57\nStatement_Details : Private Project, Open Project\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n" }, { "role": "user", "content": "For each start station id, what is its name, longitude and average duration of trips started there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.name, station.long, trip.duration, station.id, trip.start_station_id.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Studio\" TEXT, \n\t\"Director\" TEXT, \n\t\"Gross_in_dollar\" INTEGER, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/\nColumns in film and 3 examples in each column for high cardinality columns :\nFilm_ID : 1, 13, 11\nTitle : Annie, Rocky III, Tootsie\nDirector : Richard Attenborough, Nicholas Meyer, Ted Kotcheff\nGross_in_dollar : 53977250, 76606280, 125049125\n/\n/\nColumns in film and all categories for low cardinality columns :\nStudio : MGM, United Artists, Universal, 20th Century Fox, Columbia, Paramount, Columbia / Rastar, Paramount / Lorimar, Orion / Carolco, Universal / RKO\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"Official_Name\" TEXT, \n\t\"Status\" TEXT, \n\t\"Area_km_2\" REAL, \n\t\"Population\" REAL, \n\t\"Census_Ranking\" TEXT, \n\tPRIMARY KEY (\"City_ID\")\n)\n/\nColumns in city and all categories for low cardinality columns :\nCity_ID : 1, 2, 5, 4, 3\nOfficial_Name : Plaster Rock, Aroostook, Perth-Andover, Drummond, Grand Falls/Grand-Sault\nStatus : Village, Town\nArea_km_2 : 8.91, 18.06, 8.89, 2.24, 3.09\nPopulation : 351.0, 1135.0, 775.0, 1778.0, 5706.0\nCensus_Ranking : 3460 of 5008, 1936 of 5,008, 2418 of 5008, 636 of 5008, 1442 of 5,008\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n/\n \nCREATE TABLE \"Suppliers\" (\n\tsupplier_id INTEGER, \n\tsupplier_name VARCHAR(80), \n\tsupplier_phone VARCHAR(80), \n\tPRIMARY KEY (supplier_id)\n)\n/\nColumns in Suppliers and all categories for low cardinality columns :\nsupplier_id : 1, 2, 4, 3\nsupplier_name : Tesco, Lidl, AB Store, Audi\nsupplier_phone : 287-071-1153x254, (692)009-5928, 1-432-960-2402x1734, 1-483-283-4742\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE record (\n\t\"ID\" INTEGER, \n\t\"Result\" TEXT, \n\t\"Swimmer_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\tPRIMARY KEY (\"Swimmer_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Swimmer_ID\") REFERENCES swimmer (\"ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"ID\")\n)\n/\nColumns in record and 3 examples in each column for high cardinality columns :\nID : 1, 13, 11\n/\n/\nColumns in record and all categories for low cardinality columns :\nResult : Loss, Win, NC\nSwimmer_ID : 1, 2, 5, 4, 6, 3\nEvent_ID : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n/\n \nCREATE TABLE \"Problems\" (\n\tproblem_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\tclosure_authorised_by_staff_id INTEGER NOT NULL, \n\treported_by_staff_id INTEGER NOT NULL, \n\tdate_problem_reported DATETIME NOT NULL, \n\tdate_problem_closed DATETIME, \n\tproblem_description VARCHAR(255), \n\tother_problem_details VARCHAR(255), \n\tPRIMARY KEY (problem_id), \n\tFOREIGN KEY(reported_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Product\" (product_id), \n\tFOREIGN KEY(closure_authorised_by_staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Problems and 3 examples in each column for high cardinality columns :\nproblem_id : 1, 13, 11\nclosure_authorised_by_staff_id : 1, 13, 2\ndate_problem_reported : 1995-05-14 08:32:56, 1988-11-07 16:09:31, 1986-11-13 07:30:55\ndate_problem_closed : 1974-09-20 13:42:19, 1997-10-18 20:09:57, 2004-06-20 01:08:25\nproblem_description : d, i, s\n/\n/\nColumns in Problems and all categories for low cardinality columns :\nproduct_id : 1, 13, 2, 5, 7, 8, 4, 6, 15\nreported_by_staff_id : 1, 13, 11, 2, 5, 7, 4, 14, 10\nother_problem_details : f, m, i, s, k, l, p, v, c\n/\n \nCREATE TABLE invoices (\n\tid INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tinvoice_date TIMESTAMP NOT NULL, \n\tbilling_address VARCHAR(70), \n\tbilling_city VARCHAR(40), \n\tbilling_state VARCHAR(40), \n\tbilling_country VARCHAR(40), \n\tbilling_postal_code VARCHAR(10), \n\ttotal NUMERIC(10, 2) NOT NULL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(customer_id) REFERENCES customers (id)\n)\n/\nColumns in invoices and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\ncustomer_id : 53, 56, 49\ninvoice_date : 2008-09-13 00:00:00, 2007-07-11 00:00:00, 2007-10-08 00:00:00\nbilling_address : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\nbilling_city : Oslo, Lisbon, Mountain View\nbilling_state : AZ, NSW, Dublin\nbilling_country : Sweden, Australia, India\nbilling_postal_code : B3S 1C5, 85719, 1106\ntotal : 3.96, 17.91, 15.86\n/\n\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 7089 Mueller Forks, 535 Ariel Brook, 3904 Stroman Passage\ncity : Buckridgehaven, South Eugene, Elviebury\nzip_postcode : 22194, 99903, 14445\nstate_province_county : Louisiana, Kentucky, Ohio\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n" }, { "role": "user", "content": "For each station, find its latitude and the minimum duration of trips that ended at the station." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.name, station.lat, trip.duration, station.id, trip.end_station_id.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Products\" (\n\t\"Product_ID\" VARCHAR(100) NOT NULL, \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\t\"Product_Description\" VARCHAR(255), \n\t\"Other_Product_Service_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Product_ID\"), \n\tUNIQUE (\"Product_ID\")\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nProduct_ID : 250, 300, 233\nProduct_Price : 634660.0000, 1577.0000, 900.0000\n/\n/\nColumns in Products and all categories for low cardinality columns :\nProduct_Name : dinning, photo, film\nProduct_Description : None\nOther_Product_Service_Details : None\n/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n/\n \nCREATE TABLE news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n/\n/\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE competition_record (\n\t\"Competition_ID\" INTEGER, \n\t\"Farm_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Competition_ID\", \"Farm_ID\"), \n\tFOREIGN KEY(\"Farm_ID\") REFERENCES farm (\"Farm_ID\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES farm_competition (\"Competition_ID\")\n)\n/\nColumns in competition_record and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 3\nFarm_ID : 1, 2, 5, 7, 8, 4, 3\nRank : 1, 2, 4, 3\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Ref_Locations\" (\n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Location_Name\" VARCHAR(255) NOT NULL, \n\t\"Location_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Location_Code\")\n)\n/\nColumns in Ref_Locations and all categories for low cardinality columns :\nLocation_Code : b, e, n, x, c\nLocation_Name : Canada, Xiamen, Nanjing, Brazil, Edinburgh\nLocation_Description : \n/\n \nCREATE TABLE endowment (\n\tendowment_id INTEGER, \n\t\"School_id\" INTEGER, \n\tdonator_name TEXT, \n\tamount REAL, \n\tPRIMARY KEY (endowment_id), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/\nColumns in endowment and 3 examples in each column for high cardinality columns :\nendowment_id : 1, 11, 2\ndonator_name : Santo Domingo Este, Duarte, San Cristóbal\namount : 9.05, 8.82, 8.85\n/\n/\nColumns in endowment and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\n/\n \nCREATE TABLE \"Customers_Policies\" (\n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Date_Opened\" DATE, \n\t\"Date_Closed\" DATE, \n\tPRIMARY KEY (\"Customer_ID\", \"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\"), \n\tFOREIGN KEY(\"Policy_ID\") REFERENCES \"Available_Policies\" (\"Policy_ID\")\n)\n/\nColumns in Customers_Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 586, 346, 630\nDate_Opened : 2016-06-24, 2016-11-18, 2016-07-07\nDate_Closed : 2018-03-08, 2018-02-20, 2018-03-19\n/\n/\nColumns in Customers_Policies and all categories for low cardinality columns :\nCustomer_ID : 562, 582, 892, 826, 682, 214, 996, 256, 641\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n/\n/\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n/\n" }, { "role": "user", "content": "For each end station id, what is its name, latitude, and minimum duration for trips ended there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: station, trip.\nFrom these tables, I'll be using the following columns: station.name, station.lat, trip.duration, station.id, trip.end_station_id.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Roles\" (\n\trole_code VARCHAR(15), \n\trole_description VARCHAR(80), \n\tPRIMARY KEY (role_code)\n)\n/\nColumns in Roles and all categories for low cardinality columns :\nrole_code : PROJ-MGR, DBA\nrole_description : Project Manager, Database Administrator\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Team\" (\n\tid INTEGER, \n\tteam_api_id INTEGER, \n\tteam_fifa_api_id INTEGER, \n\tteam_long_name TEXT, \n\tteam_short_name TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in Team and 3 examples in each column for high cardinality columns :\nid : 9553, 14876, 9547\nteam_api_id : 9761, 9875, 9847\nteam_fifa_api_id : 65, 1907, 1926\nteam_long_name : Lecce, AS Saint-Étienne, Stade Rennais FC\nteam_short_name : SIE, NIC, BAS\n/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE enrollments (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"TotalEnrollment_AY\" INTEGER, \n\t\"FTE_AY\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Year\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in enrollments and 3 examples in each column for high cardinality columns :\nYear : 1979, 2004, 1937\nTotalEnrollment_AY : 495, 5734, 9547\nFTE_AY : 3877, 14324, 12876\n/\n/\nColumns in enrollments and all categories for low cardinality columns :\nCampus : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n/\n \nCREATE TABLE \"Claims_Processing\" (\n\t\"Claim_Processing_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Claim_Outcome_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Staff_ID\" INTEGER, \n\tPRIMARY KEY (\"Claim_Processing_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Processing and 3 examples in each column for high cardinality columns :\nClaim_Processing_ID : 243, 342, 818\n/\n/\nColumns in Claims_Processing and all categories for low cardinality columns :\nClaim_ID : 45, 28, 90, 24, 34, 62, 15, 27, 81\nClaim_Outcome_Code : Settled, In progress, Disputed\nClaim_Stage_ID : 1, 3\nStaff_ID : 771, 427, 510, 673, 986, 687, 822, 589, 718\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE stadium (\n\tid INTEGER, \n\tname TEXT, \n\t\"Home_Games\" INTEGER, \n\t\"Average_Attendance\" REAL, \n\t\"Total_Attendance\" REAL, \n\t\"Capacity_Percentage\" REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in stadium and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Gillette Stadium, Lincoln Financial Field, New Meadowlands Stadium\nAverage_Attendance : 70038.0, 87047.0, 71227.0\nTotal_Attendance : 553144.0, 566362.0, 550048.0\n/\n/\nColumns in stadium and all categories for low cardinality columns :\nHome_Games : 8\nCapacity_Percentage : 96.0, 108.8, 100.3, 100.0, 95.8, 90.7, 102.3, 98.4, 97.1, 95.3\n/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n/\n" }, { "role": "user", "content": "List all the distinct stations from which a trip of duration below 100 started." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, duration.\nThe SQL query I'll be generating is:\nSELECT DISTINCT start_station_name FROM trip WHERE duration < 100" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Albums\" (\n\t\"AId\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Label\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"AId\")\n)\n/\nColumns in Albums and all categories for low cardinality columns :\nAId : \nTitle : \nYear : \nLabel : \nType : \n/\n \nCREATE TABLE \"Organisations\" (\n\torganisation_id INTEGER, \n\torganisation_type VARCHAR(10) NOT NULL, \n\torganisation_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (organisation_id), \n\tFOREIGN KEY(organisation_type) REFERENCES \"Organisation_Types\" (organisation_type)\n)\n/\nColumns in Organisations and 3 examples in each column for high cardinality columns :\norganisation_id : 1, 13, 11\norganisation_details : itaque, eveniet, consequuntur\n/\n/\nColumns in Organisations and all categories for low cardinality columns :\norganisation_type : RES, SPON\n/\n \nCREATE TABLE airlines (\n\talid INTEGER, \n\tname TEXT, \n\tiata VARCHAR(2), \n\ticao VARCHAR(3), \n\tcallsign TEXT, \n\tcountry TEXT, \n\tactive VARCHAR(2), \n\tPRIMARY KEY (alid)\n)\n/\nColumns in airlines and 3 examples in each column for high cardinality columns :\nalid : 87, 56, 65\nname : Arab Agricultural Aviation Company, Avion Taxi, Amadeus Global Travel Distribution\niata : , U3, JP\nicao : , ADP, UVS\ncallsign : , ALGOMA, SECUREX\ncountry : , Afghanistan, Gabon\n/\n/\nColumns in airlines and all categories for low cardinality columns :\nactive : Y, N\n/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"White\" REAL, \n\t\"Black\" REAL, \n\t\"Amerindian\" REAL, \n\t\"Asian\" REAL, \n\t\"Multiracial\" REAL, \n\t\"Hispanic\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"County_ID\") REFERENCES county_public_safety (\"County_ID\")\n)\n/\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 16, 13\nName : Aguadilla, Barranquitas, Bayamón\nWhite : 70.7, 78.3, 93.1\nBlack : 4.1, 22.8, 7.2\nMultiracial : 10.7, 12.1, 11.7\n/\n/\nColumns in city and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nAmerindian : 0.4, 0.6, 1.0, 0.3, 0.2, 0.9\nAsian : 0.1, 0.4, 0.3, 0.0, 0.2\nHispanic : 99.6, 98.5, 99.1, 99.5, 99.2, 99.4, 98.6, 98.9, 99.0, 99.3\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE airport (\n\t\"Airport_ID\" INTEGER, \n\t\"Airport_Name\" TEXT, \n\t\"Total_Passengers\" REAL, \n\t\"%_Change_2007\" TEXT, \n\t\"International_Passengers\" REAL, \n\t\"Domestic_Passengers\" REAL, \n\t\"Transit_Passengers\" REAL, \n\t\"Aircraft_Movements\" REAL, \n\t\"Freight_Metric_Tonnes\" REAL, \n\tPRIMARY KEY (\"Airport_ID\")\n)\n/\nColumns in airport and all categories for low cardinality columns :\nAirport_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAirport_Name : Bristol, London Luton, East Midlands, Birmingham Airport, Glasgow International, London Stansted, London Heathrow, London Gatwick, Edinburgh, Manchester\nTotal_Passengers : 8178891.0, 5620673.0, 34205887.0, 9627589.0, 67054745.0, 6267114.0, 10180734.0, 21219195.0, 22360364.0, 9006702.0\n%_Change_2007 : 2.6%, 4.0%, 6.0%, 1.5%, 0.5%, 5.7%, 2.9%, 4.3%, 3.8%, 7.0%\nInternational_Passengers : 3711140.0, 8105162.0, 3943139.0, 19996947.0, 5057051.0, 4870184.0, 8853224.0, 61344438.0, 30431051.0, 18119230.0\nDomestic_Passengers : 746094.0, 5562516.0, 1171605.0, 2943719.0, 1471538.0, 4192121.0, 3730963.0, 1320678.0, 2343428.0, 5281038.0\nTransit_Passengers : 156246.0, 50889.0, 6832.0, 19989.0, 43873.0, 43631.0, 14524.0, 38458.0, 4395.0, 147791.0\nAircraft_Movements : 478693.0, 117859.0, 204610.0, 193282.0, 125550.0, 76517.0, 112227.0, 100087.0, 93038.0, 263653.0\nFreight_Metric_Tonnes : 3.0, 261507.0, 12418.0, 40518.0, 197738.0, 141781.0, 107702.0, 3546.0, 12192.0, 1397054.0\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE competition_result (\n\t\"Competition_ID\" INTEGER, \n\t\"Club_ID_1\" INTEGER, \n\t\"Club_ID_2\" INTEGER, \n\t\"Score\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\", \"Club_ID_1\", \"Club_ID_2\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES competition (\"Competition_ID\"), \n\tFOREIGN KEY(\"Club_ID_2\") REFERENCES club (\"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID_1\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in competition_result and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 10\nClub_ID_1 : 1, 4, 3\nClub_ID_2 : 2, 4, 6\nScore : 11:10, 10:11, 10:3, 13:10, 12:9, 25:2\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_category VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : Coffee Bean, Learning French, Four Seasons\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_category : Food, Books, Electronics, Hardware\n/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n/\n" }, { "role": "user", "content": "What are all the different start station names for a trip that lasted less than 100?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: start_station_name, duration.\nThe SQL query I'll be generating is:\nSELECT DISTINCT start_station_name FROM trip WHERE duration < 100" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n/\n/\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n/\n/\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n/\n/\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\tprevious_transaction_id INTEGER, \n\taccount_id INTEGER NOT NULL, \n\tcard_id INTEGER NOT NULL, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DOUBLE, \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(card_id) REFERENCES \"Customers_Cards\" (card_id)\n)\n/\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\nprevious_transaction_id : 925, 947, 986\naccount_id : 1, 13, 11\ntransaction_date : 2018-03-24 10:39:09, 2018-03-23 21:59:28, 2018-03-24 05:45:57\ntransaction_amount : 486.56, 1336.21, 945.43\n/\n/\nColumns in Financial_Transactions and all categories for low cardinality columns :\ncard_id : 1, 11, 2, 5, 7, 4, 6, 12, 3, 9\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n/\n \nCREATE TABLE \"Staff\" (\n\t\"Staff_ID\" INTEGER NOT NULL, \n\t\"Staff_Details\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Staff_ID\")\n)\n/\nColumns in Staff and 3 examples in each column for high cardinality columns :\nStaff_ID : 510, 427, 771\nStaff_Details : Gideon, Vernie, Roman\n/\n\n \nCREATE TABLE \"Photos\" (\n\t\"Photo_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Filename\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Photo_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Photos and 3 examples in each column for high cardinality columns :\nPhoto_ID : 428, 303, 332\nTourist_Attraction_ID : 5076, 6523, 5265\nName : fun3, din2, park1\nFilename : 863, 695, 392\n/\n/\nColumns in Photos and all categories for low cardinality columns :\nDescription : None\nOther_Details : None\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 7089 Mueller Forks, 535 Ariel Brook, 3904 Stroman Passage\ncity : Buckridgehaven, South Eugene, Elviebury\nzip_postcode : 22194, 99903, 14445\nstate_province_county : Louisiana, Kentucky, Ohio\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"Parking_Fines\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/\nColumns in Parking_Fines and all categories for low cardinality columns :\ncouncil_tax_id : 10, 9\ncmi_cross_ref_id : 4, 81\n/\n \nCREATE TABLE \"Ref_Calendar\" (\n\t\"Calendar_Date\" DATETIME NOT NULL, \n\t\"Day_Number\" INTEGER, \n\tPRIMARY KEY (\"Calendar_Date\")\n)\n/\nColumns in Ref_Calendar and 3 examples in each column for high cardinality columns :\nCalendar_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1972-03-31 09:47:22\n/\n/\nColumns in Ref_Calendar and all categories for low cardinality columns :\nDay_Number : 1, 2, 5, 7, 8, 3, 9\n/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n" }, { "role": "user", "content": "Find all the zip codes in which the max dew point have never reached 70." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, max_dew_point_f.\nThe SQL query I'll be generating is:\nSELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n/\n/\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n/\n \nCREATE TABLE \"PROFESSOR\" (\n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"PROF_OFFICE\" VARCHAR(50), \n\t\"PROF_EXTENSION\" VARCHAR(4), \n\t\"PROF_HIGH_DEGREE\" VARCHAR(5), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/\nColumns in PROFESSOR and 3 examples in each column for high cardinality columns :\nEMP_NUM : 387, 301, 155\nDEPT_CODE : ECON/FIN, ART, HIST\nPROF_OFFICE : KLR 203E, BBG 208, AAK 230\nPROF_EXTENSION : 2248, 2851, 4436\n/\n/\nColumns in PROFESSOR and all categories for low cardinality columns :\nPROF_HIGH_DEGREE : Ph.D., MBA, MA, DBA\n/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(20), \n\tproduct_price DECIMAL(19, 4), \n\tproduct_description VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 4, 6, 3\nproduct_name : electronics, food, dvds, cloth, gift, books\nproduct_price : 5022.3900, 3644.4500, 1322.7800, 2511.2900, 7111.6800, 6402.0900\nproduct_description : great condition, bad condition, good condition\n/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n/\n \nCREATE TABLE \"Customer_Contact_Channels\" (\n\tcustomer_id INTEGER NOT NULL, \n\tchannel_code VARCHAR(15) NOT NULL, \n\tactive_from_date DATETIME NOT NULL, \n\tactive_to_date DATETIME, \n\tcontact_number VARCHAR(50) NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/\nColumns in Customer_Contact_Channels and 3 examples in each column for high cardinality columns :\nactive_from_date : 2017-05-25 16:08:45, 2017-06-21 06:41:19, 2018-03-01 10:17:18\nactive_to_date : 2018-03-16 14:00:15, 2018-02-24 00:57:39, 2018-03-20 14:01:12\ncontact_number : 940.035.6435x0225, 846.043.4809x0426, 1-968-863-4947x96956\n/\n/\nColumns in Customer_Contact_Channels and all categories for low cardinality columns :\ncustomer_id : 13, 2, 5, 15, 4, 6, 14, 3, 10, 9\nchannel_code : Mobile, Email, Fax, Handheld, Cell\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"CHECKING\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/\nColumns in CHECKING and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nbalance : 3000.0, 10000.0, 2000.0, 7.0, 7000.0, 77.0\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Organisations\" (\n\torganisation_id INTEGER, \n\torganisation_type VARCHAR(10) NOT NULL, \n\torganisation_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (organisation_id), \n\tFOREIGN KEY(organisation_type) REFERENCES \"Organisation_Types\" (organisation_type)\n)\n/\nColumns in Organisations and 3 examples in each column for high cardinality columns :\norganisation_id : 1, 13, 11\norganisation_details : itaque, eveniet, consequuntur\n/\n/\nColumns in Organisations and all categories for low cardinality columns :\norganisation_type : RES, SPON\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n \nCREATE TABLE \"Project_Staff\" (\n\tstaff_id DOUBLE, \n\tproject_id INTEGER NOT NULL, \n\trole_code VARCHAR(10) NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Staff_Roles\" (role_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/\nColumns in Project_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 3.0, 5137097.0, 45.0\ndate_from : 1981-10-04 22:44:50, 2000-08-28 11:49:17, 2005-01-13 11:49:48\ndate_to : 1988-03-04 19:30:05, 2004-07-28 03:11:47, 1971-07-19 22:49:05\n/\n/\nColumns in Project_Staff and all categories for low cardinality columns :\nproject_id : 1, 11, 2, 5, 7, 8, 4, 3, 15, 9\nrole_code : researcher, leader\nother_details : None\n/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n/\n" }, { "role": "user", "content": "What are all the different zip codes that have a maximum dew point that was always below 70?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: zip_code, max_dew_point_f.\nThe SQL query I'll be generating is:\nSELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE party (\n\t\"Party_ID\" INTEGER, \n\t\"Minister\" TEXT, \n\t\"Took_office\" TEXT, \n\t\"Left_office\" TEXT, \n\t\"Region_ID\" INTEGER, \n\t\"Party_name\" TEXT, \n\tPRIMARY KEY (\"Party_ID\"), \n\tFOREIGN KEY(\"Region_ID\") REFERENCES region (\"Region_ID\")\n)\n/\nColumns in party and all categories for low cardinality columns :\nParty_ID : 1, 2, 5, 4, 3\nMinister : Kojo Botsio (MP), Ebenezer Ako-Adjei (MP), Dr. Kwame Nkrumah (MP), Imoru Egala (MP)\nTook_office : 1958, 1961, 1959, 1960, 1957\nLeft_office : 1962, 1958, 1961, 1959, 1960\nRegion_ID : 1, 2, 5, 4, 3\nParty_name : Convention Peoples Party, Sinefine Party, Convention Union Party, 3, Progress Party\n/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tpayment_method VARCHAR(15) NOT NULL, \n\tcustomer_name VARCHAR(80), \n\tcustomer_phone VARCHAR(80), \n\tcustomer_email VARCHAR(80), \n\tcustomer_address VARCHAR(255), \n\tcustomer_login VARCHAR(80), \n\tcustomer_password VARCHAR(10), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : Kyle, Ruthie, Elvera\ncustomer_phone : 698-327-5792, +66(7)1491041398, 203-036-0511x96487\ncustomer_email : kristina85@example.org, davis.rosamond@example.net, marc.schiller@example.com\ncustomer_address : 80569 Crona Path Suite 165, 5514 Ophelia Cliffs Apt. 266, 56955 Desmond Lake Apt. 120\ncustomer_password : 9dc50bc5b6, f64f0fd096, 0b9f651030\n/\n/\nColumns in Customers and all categories for low cardinality columns :\npayment_method : Credit Card, Direct Debit\ncustomer_login : None\n/\n \nCREATE TABLE hosting_city (\n\t\"Year\" INTEGER, \n\t\"Match_ID\" INTEGER, \n\t\"Host_City\" TEXT, \n\tPRIMARY KEY (\"Year\"), \n\tFOREIGN KEY(\"Match_ID\") REFERENCES \"match\" (\"Match_ID\"), \n\tFOREIGN KEY(\"Host_City\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in hosting_city and all categories for low cardinality columns :\nYear : 2009, 2013, 2012, 2008, 2011, 2010\nMatch_ID : 1, 2, 5, 4, 6, 3\nHost_City : 1, 11, 2, 6, 12\n/\n \nCREATE TABLE department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n/\n/\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n/\n \nCREATE TABLE broadcast (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Time_of_day\" TEXT, \n\tPRIMARY KEY (\"Channel_ID\", \"Program_ID\"), \n\tFOREIGN KEY(\"Program_ID\") REFERENCES program (\"Program_ID\"), \n\tFOREIGN KEY(\"Channel_ID\") REFERENCES channel (\"Channel_ID\")\n)\n/\nColumns in broadcast and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nProgram_ID : 1, 2, 4, 3\nTime_of_day : Morning, Night, Noon\n/\n \nCREATE TABLE \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\n/\n" }, { "role": "user", "content": "Find the id for the trips that lasted at least as long as the average duration of trips in zip code 94103." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration, zip_code.\nThe SQL query I'll be generating is:\nSELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n \nCREATE TABLE screen_mode (\n\t\"Graphics_mode\" REAL, \n\t\"Char_cells\" TEXT, \n\t\"Pixels\" TEXT, \n\t\"Hardware_colours\" REAL, \n\tused_kb REAL, \n\tmap TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"Graphics_mode\")\n)\n/\nColumns in screen_mode and all categories for low cardinality columns :\nGraphics_mode : 3.0, 1.0, 0.0, 2.0, 6.0, 4.0, 5.0\nChar_cells : 40 × 32, 20 × 32, 80 × 25, 40 × 25, 80 × 32\nPixels : 320 × 200, 640 × 200, 320 × 256, 640 × 256, 160 × 256\nHardware_colours : 8.0, 2.0, 4.0\nused_kb : 8.0, 10.0, 16.0, 20.0\nmap : 4000–7FFF, 3000–7FFF, 5800–7FFF, 6000–7FFF\nType : Text, Graphics\n/\n \nCREATE TABLE department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n/\n \nCREATE TABLE \"Images\" (\n\timage_id INTEGER, \n\timage_alt_text VARCHAR(80), \n\timage_name VARCHAR(40), \n\timage_url VARCHAR(255), \n\tPRIMARY KEY (image_id)\n)\n/\nColumns in Images and 3 examples in each column for high cardinality columns :\nimage_id : 1, 13, 11\nimage_alt_text : Chaya, Ashtyn, Marianna\nimage_name : chapter3, data1, data2\nimage_url : http://www.bernierconnelly.com/1.jpg, http://www.hermann.com/1.jpg, http://connellykertzmann.org/1.jpg\n/\n\n \nCREATE TABLE technician (\n\ttechnician_id REAL, \n\t\"Name\" TEXT, \n\t\"Team\" TEXT, \n\t\"Starting_Year\" REAL, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (technician_id)\n)\n/\nColumns in technician and all categories for low cardinality columns :\ntechnician_id : 3.0, 8.0, 10.0, 1.0, 7.0, 2.0, 6.0, 9.0, 4.0, 5.0\nName : Mark Sewell, John Brown, Mickey Cochrane, Joe Sewell, Tony Sewell, Joe Cochrane, Eddie Collins, Charlie Hollocher, Lou Boudreau\nTeam : CHC, NYY, CLE, PHA, CWS\nStarting_Year : 2013.0, 2016.0, 2003.0, 2006.0, 2005.0, 2002.0, 2009.0, 2012.0\nAge : 38, 37, 45, 46, 28, 36, 32, 47, 43, 35\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n/\n/\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE \"Undergoes\" (\n\t\"Patient\" INTEGER NOT NULL, \n\t\"Procedures\" INTEGER NOT NULL, \n\t\"Stay\" INTEGER NOT NULL, \n\t\"DateUndergoes\" DATETIME NOT NULL, \n\t\"Physician\" INTEGER NOT NULL, \n\t\"AssistingNurse\" INTEGER, \n\tPRIMARY KEY (\"Patient\", \"Procedures\", \"Stay\", \"DateUndergoes\"), \n\tCONSTRAINT \"fk_Undergoes_Patient_SSN\" FOREIGN KEY(\"Patient\") REFERENCES \"Patient\" (\"SSN\"), \n\tCONSTRAINT \"fk_Undergoes_Procedures_Code\" FOREIGN KEY(\"Procedures\") REFERENCES \"Procedures\" (\"Code\"), \n\tCONSTRAINT \"fk_Undergoes_Stay_StayID\" FOREIGN KEY(\"Stay\") REFERENCES \"Stay\" (\"StayID\"), \n\tCONSTRAINT \"fk_Undergoes_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Undergoes_Nurse_EmployeeID\" FOREIGN KEY(\"AssistingNurse\") REFERENCES \"Nurse\" (\"EmployeeID\")\n)\n/\nColumns in Undergoes and all categories for low cardinality columns :\nPatient : 100000001, 100000004\nProcedures : 1, 2, 5, 7, 4, 6\nStay : 3215, 3217\nDateUndergoes : 2008-05-09 00:00:00, 2008-05-10 00:00:00, 2008-05-13 00:00:00, 2008-05-03 00:00:00, 2008-05-02 00:00:00, 2008-05-07 00:00:00\nPhysician : 7, 6, 3\nAssistingNurse : 102, 101, 105, 103\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n" }, { "role": "user", "content": "What are the ids of all trips that had a duration as long as the average trip duration in the zip code 94103?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: trip.\nFrom these tables, I'll be using the following columns: id, duration, zip_code.\nThe SQL query I'll be generating is:\nSELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103)" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE playlists (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/\nColumns in playlists and 3 examples in each column for high cardinality columns :\nid : 1, 16, 13\nname : Heavy Metal Classic, 90’s Music, Classical 101 - Deep Cuts\n/\n\n \nCREATE TABLE college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE \"Settlements\" (\n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER, \n\t\"Effective_Date\" DATE, \n\t\"Settlement_Amount\" REAL, \n\tPRIMARY KEY (\"Settlement_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claims\" (\"Claim_ID\"), \n\tUNIQUE (\"Settlement_ID\")\n)\n/\nColumns in Settlements and all categories for low cardinality columns :\nSettlement_ID : 616, 543, 205, 544, 628, 393, 161, 208, 176, 604\nClaim_ID : 428, 309, 717, 145, 228, 311, 360, 134, 641, 604\nEffective_Date : 2009-11-20, 1978-09-09, 1973-10-27, 1971-06-29, 1995-04-02, 2006-04-19, 2014-12-09, 2001-07-02, 2003-12-28, 1972-03-02\nSettlement_Amount : 8013.95, 8827.06, 9164.1, 2138.96, 2722.67, 1721.17, 1588.45, 9814.39, 3101.3, 6451.65\n/\n \nCREATE TABLE exhibition_record (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Exhibition_ID\", \"Date\"), \n\tFOREIGN KEY(\"Exhibition_ID\") REFERENCES exhibition (\"Exhibition_ID\")\n)\n/\nColumns in exhibition_record and 3 examples in each column for high cardinality columns :\nDate : February 25, February 19, December 2\nAttendance : 1313, 24808, 1233\n/\n/\nColumns in exhibition_record and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n/\n \nCREATE TABLE furniture (\n\t\"Furniture_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Num_of_Component\" INTEGER, \n\t\"Market_Rate\" REAL, \n\tPRIMARY KEY (\"Furniture_ID\")\n)\n/\nColumns in furniture and all categories for low cardinality columns :\nFurniture_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dining set, Chabudai, Billiard table, Hatstand, Bookcase, Four-poster bed, Bench\nNum_of_Component : 5, 4, 6, 14, 3, 12\nMarket_Rate : 1.0, 3.5, 52.5, 0.5, 40.0, 2.0\n/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n/\n/\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n/\n/\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n/\n/\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE faculty (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Faculty\" REAL, \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in faculty and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nFaculty : 449.8, 117.7, 1027.6\n/\n/\nColumns in faculty and all categories for low cardinality columns :\nYear : 2002, 2003, 2004\n/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n/\n/\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n/\n/\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n/\n/\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n/\n \nCREATE TABLE status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\n/\n \nCREATE TABLE \"Activity\" (\n\tactid INTEGER, \n\tactivity_name VARCHAR(25), \n\tPRIMARY KEY (actid)\n)\n/\nColumns in Activity and 3 examples in each column for high cardinality columns :\nactid : 771, 782, 770\nactivity_name : Proselytizing, Spelunking, Extreme Canasta\n/\n\n \nCREATE TABLE mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\n/\n" }, { "role": "user", "content": "What are the dates in which the mean sea level pressure was between 30.3 and 31?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: weather.\nFrom these tables, I'll be using the following columns: mean_sea_level_pressure_inches.\nThe SQL query I'll be generating is:\nSELECT date FROM weather WHERE mean_sea_level_pressure_inches BETWEEN 30.3 AND 31" } ]