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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 39 new columns ({'Youth 15-24', 'Child 0-14', 'Pop - Males', 'Pop - Females', 'Pop 60 - 64 years', 'Pop 80 - 84 years', 'Neighbourhood Id', 'Pop 75 - 79 years', 'Pop 65 - 69 years', 'Seniors 65 and over', 'Pop  25 - 29 years', 'Pop 40 - 44 years', 'Pop 30 - 34 years', '   Language - Russian', '   Language - Persian (Farsi)', '   Language - Portuguese', 'Pop 50 - 54 years', '   Language - Spanish', 'Pop 20 - 24 years', 'Pop 15 -19 years', 'Pop 35 - 39 years', 'Seniors 55 and over', '   Language - Chinese', '   Language - Urdu', 'Home Language Category', 'Pop 10 - 14 years', '   Language - Tagalog', 'Pop 70 - 74 years', 'Pop 85 years and over', '   Language - Italian', 'Total Area', 'Neighbourhood', 'Pop 0 - 4 years', 'Pop 45 - 49 years', '   Language - Tamil', 'Total Population', 'Pop 55 - 59 years', '   Language - Korean', 'Pop 5 - 9 years'}) and 15 missing columns ({'Client Gender', 'Classification', 'FSA', 'Source of Infection', 'Age Group', 'Assigned_ID', 'Reported Date', 'Ever Hospitalized', 'Ever in ICU', 'Neighbourhood Name', 'Episode Date', 'Ever Intubated', '_id', 'Outcome', 'Outbreak Associated'}).

This happened while the csv dataset builder was generating data using

hf://datasets/fadingNA/CovidCases.csv/WB-demographic.csv (at revision 86f234522d3e5d8ed72dce1d2b0f1dbc5cbf439d)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Neighbourhood: string
              Neighbourhood Id: int64
              Total Area: double
              Total Population: int64
              Pop - Males: int64
              Pop - Females: int64
              Pop 0 - 4 years: int64
              Pop 5 - 9 years: int64
              Pop 10 - 14 years: int64
              Pop 15 -19 years: int64
              Pop 20 - 24 years: int64
              Pop  25 - 29 years: int64
              Pop 30 - 34 years: int64
              Pop 35 - 39 years: int64
              Pop 40 - 44 years: int64
              Pop 45 - 49 years: int64
              Pop 50 - 54 years: int64
              Pop 55 - 59 years: int64
              Pop 60 - 64 years: int64
              Pop 65 - 69 years: int64
              Pop 70 - 74 years: int64
              Pop 75 - 79 years: int64
              Pop 80 - 84 years: int64
              Pop 85 years and over: int64
              Seniors 55 and over: int64
              Seniors 65 and over: int64
              Child 0-14: int64
              Youth 15-24: int64
              Home Language Category: int64
                 Language - Chinese: int64
                 Language - Italian: int64
                 Language - Korean: int64
                 Language - Persian (Farsi): int64
                 Language - Portuguese: int64
                 Language - Russian: int64
                 Language - Spanish: int64
                 Language - Tagalog: int64
                 Language - Tamil: int64
                 Language - Urdu: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 5413
              to
              {'_id': Value(dtype='int64', id=None), 'Assigned_ID': Value(dtype='int64', id=None), 'Outbreak Associated': Value(dtype='string', id=None), 'Age Group': Value(dtype='string', id=None), 'Neighbourhood Name': Value(dtype='string', id=None), 'FSA': Value(dtype='string', id=None), 'Source of Infection': Value(dtype='string', id=None), 'Classification': Value(dtype='string', id=None), 'Episode Date': Value(dtype='string', id=None), 'Reported Date': Value(dtype='string', id=None), 'Client Gender': Value(dtype='string', id=None), 'Outcome': Value(dtype='string', id=None), 'Ever Hospitalized': Value(dtype='string', id=None), 'Ever in ICU': Value(dtype='string', id=None), 'Ever Intubated': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 39 new columns ({'Youth 15-24', 'Child 0-14', 'Pop - Males', 'Pop - Females', 'Pop 60 - 64 years', 'Pop 80 - 84 years', 'Neighbourhood Id', 'Pop 75 - 79 years', 'Pop 65 - 69 years', 'Seniors 65 and over', 'Pop  25 - 29 years', 'Pop 40 - 44 years', 'Pop 30 - 34 years', '   Language - Russian', '   Language - Persian (Farsi)', '   Language - Portuguese', 'Pop 50 - 54 years', '   Language - Spanish', 'Pop 20 - 24 years', 'Pop 15 -19 years', 'Pop 35 - 39 years', 'Seniors 55 and over', '   Language - Chinese', '   Language - Urdu', 'Home Language Category', 'Pop 10 - 14 years', '   Language - Tagalog', 'Pop 70 - 74 years', 'Pop 85 years and over', '   Language - Italian', 'Total Area', 'Neighbourhood', 'Pop 0 - 4 years', 'Pop 45 - 49 years', '   Language - Tamil', 'Total Population', 'Pop 55 - 59 years', '   Language - Korean', 'Pop 5 - 9 years'}) and 15 missing columns ({'Client Gender', 'Classification', 'FSA', 'Source of Infection', 'Age Group', 'Assigned_ID', 'Reported Date', 'Ever Hospitalized', 'Ever in ICU', 'Neighbourhood Name', 'Episode Date', 'Ever Intubated', '_id', 'Outcome', 'Outbreak Associated'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/fadingNA/CovidCases.csv/WB-demographic.csv (at revision 86f234522d3e5d8ed72dce1d2b0f1dbc5cbf439d)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

_id
int64
Assigned_ID
int64
Outbreak Associated
string
Age Group
string
Neighbourhood Name
string
FSA
string
Source of Infection
string
Classification
string
Episode Date
string
Reported Date
string
Client Gender
string
Outcome
string
Ever Hospitalized
string
Ever in ICU
string
Ever Intubated
string
1
1
NO
50 to 59 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-01-22
2020-01-23
FEMALE
RESOLVED
No
No
No
2
2
NO
50 to 59 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-01-21
2020-01-23
MALE
RESOLVED
Yes
No
No
3
3
NO
20 to 29 Years
Parkwoods-Donalda
M3A
Travel
CONFIRMED
2020-02-05
2020-02-21
FEMALE
RESOLVED
No
No
No
4
4
NO
60 to 69 Years
Church-Yonge Corridor
M4W
Travel
CONFIRMED
2020-02-16
2020-02-25
FEMALE
RESOLVED
No
No
No
5
5
NO
60 to 69 Years
Church-Yonge Corridor
M4W
Travel
CONFIRMED
2020-02-20
2020-02-26
MALE
RESOLVED
No
No
No
6
6
NO
50 to 59 Years
Newtonbrook West
M2R
Travel
CONFIRMED
2020-02-24
2020-02-27
MALE
RESOLVED
No
No
No
7
7
NO
80 to 89 Years
Milliken
M1V
Travel
CONFIRMED
2020-02-20
2020-02-28
MALE
RESOLVED
No
No
No
8
8
NO
60 to 69 Years
Willowdale West
M2N
Travel
CONFIRMED
2020-02-21
2020-03-04
MALE
RESOLVED
Yes
No
No
9
9
NO
50 to 59 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-02-29
2020-02-29
MALE
RESOLVED
No
No
No
10
10
NO
60 to 69 Years
Henry Farm
M2J
Travel
CONFIRMED
2020-02-26
2020-03-01
MALE
RESOLVED
No
No
No
11
11
NO
70 to 79 Years
Don Valley Village
M2J
Travel
CONFIRMED
2020-02-14
2020-03-01
FEMALE
RESOLVED
No
No
No
12
12
NO
50 to 59 Years
Lawrence Park South
M4R
Travel
PROBABLE
2020-03-01
2020-03-02
MALE
RESOLVED
No
No
No
13
13
NO
60 to 69 Years
Bridle Path-Sunnybrook-York Mills
M2L
Travel
CONFIRMED
2020-03-02
2020-03-03
MALE
RESOLVED
No
No
No
14
14
NO
30 to 39 Years
Moss Park
M5A
Community
PROBABLE
2020-03-03
2020-03-04
MALE
RESOLVED
No
No
No
15
15
NO
40 to 49 Years
Annex
M6G
Travel
CONFIRMED
2020-03-02
2020-03-05
MALE
RESOLVED
No
No
No
16
16
NO
50 to 59 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-03-03
2020-03-05
MALE
RESOLVED
No
No
No
17
18
NO
40 to 49 Years
Leaside-Bennington
M4G
Travel
CONFIRMED
2020-03-04
2020-03-07
FEMALE
RESOLVED
No
No
No
18
19
YES
40 to 49 Years
Moss Park
M5A
Outbreaks, Congregate Settings
CONFIRMED
2020-03-06
2020-03-06
MALE
RESOLVED
Yes
No
No
19
20
NO
60 to 69 Years
St.Andrew-Windfields
M2P
Travel
CONFIRMED
2020-03-05
2020-03-07
MALE
RESOLVED
No
No
No
20
21
NO
80 to 89 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-03-03
2020-03-08
MALE
RESOLVED
No
No
No
21
22
NO
70 to 79 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-03-03
2020-03-08
FEMALE
RESOLVED
No
No
No
22
23
NO
60 to 69 Years
Malvern
M1B
Travel
CONFIRMED
2020-03-04
2020-03-08
FEMALE
RESOLVED
Yes
Yes
Yes
23
25
NO
40 to 49 Years
High Park North
M6P
Travel
CONFIRMED
2020-03-02
2020-03-09
MALE
RESOLVED
No
No
No
24
26
NO
30 to 39 Years
Waterfront Communities-The Island
M5V
Travel
CONFIRMED
2020-03-03
2020-03-10
MALE
RESOLVED
No
No
No
25
27
NO
20 to 29 Years
Leaside-Bennington
M4G
Close Contact
CONFIRMED
2020-03-09
2020-03-10
MALE
RESOLVED
No
No
No
26
28
NO
20 to 29 Years
null
null
Travel
PROBABLE
2020-03-02
2020-03-10
MALE
RESOLVED
No
No
No
27
29
NO
40 to 49 Years
Mimico (includes Humber Bay Shores)
M8Y
Travel
CONFIRMED
2020-03-07
2020-03-11
FEMALE
RESOLVED
No
No
No
28
30
NO
40 to 49 Years
Danforth-East York
M4J
Travel
CONFIRMED
2020-03-09
2020-03-11
MALE
RESOLVED
No
No
No
29
31
NO
70 to 79 Years
Princess-Rosethorn
M9B
Travel
CONFIRMED
2020-02-28
2020-03-11
MALE
RESOLVED
No
No
No
30
32
NO
19 and younger
Willowdale East
M2N
Close Contact
CONFIRMED
2020-03-09
2020-03-10
MALE
RESOLVED
No
No
No
31
33
NO
30 to 39 Years
Willowdale East
M2N
Close Contact
CONFIRMED
2020-03-10
2020-03-10
FEMALE
RESOLVED
No
No
No
32
35
NO
30 to 39 Years
Willowdale East
M2N
Close Contact
CONFIRMED
2020-03-10
2020-03-11
MALE
RESOLVED
No
No
No
33
36
NO
20 to 29 Years
Long Branch
M8W
Travel
CONFIRMED
2020-03-07
2020-03-11
FEMALE
RESOLVED
No
No
No
34
37
NO
30 to 39 Years
Dovercourt-Wallace Emerson-Junction
M6H
Travel
PROBABLE
2020-03-04
2020-03-09
FEMALE
RESOLVED
No
No
No
35
38
NO
19 and younger
Dovercourt-Wallace Emerson-Junction
M6H
Travel
CONFIRMED
2020-03-09
2020-03-11
FEMALE
RESOLVED
Yes
No
No
36
39
NO
60 to 69 Years
Mount Pleasant West
M4S
Travel
CONFIRMED
2020-03-08
2020-03-12
MALE
RESOLVED
Yes
No
No
37
40
NO
30 to 39 Years
Oakwood Village
M6E
Travel
PROBABLE
2020-03-09
2020-03-11
FEMALE
RESOLVED
No
No
No
38
41
NO
20 to 29 Years
South Parkdale
M6K
Community
PROBABLE
2020-03-09
2020-03-10
FEMALE
RESOLVED
No
No
No
39
42
NO
20 to 29 Years
Mount Pleasant East
M4S
Travel
CONFIRMED
2020-03-11
2020-03-11
MALE
RESOLVED
No
No
No
40
43
NO
60 to 69 Years
Mount Pleasant East
M4S
Travel
CONFIRMED
2020-03-03
2020-03-11
MALE
RESOLVED
No
No
No
41
44
NO
70 to 79 Years
Annex
M5R
Travel
CONFIRMED
2020-03-10
2020-03-11
FEMALE
RESOLVED
No
No
No
42
45
NO
60 to 69 Years
Bridle Path-Sunnybrook-York Mills
M4N
Travel
CONFIRMED
2020-03-03
2020-03-11
FEMALE
RESOLVED
No
No
No
43
46
NO
70 to 79 Years
Mount Pleasant West
M4P
Travel
CONFIRMED
2020-03-10
2020-03-12
FEMALE
RESOLVED
No
No
No
44
47
NO
80 to 89 Years
Mount Pleasant West
M4P
Travel
CONFIRMED
2020-03-02
2020-03-12
MALE
RESOLVED
No
No
No
45
48
NO
40 to 49 Years
North Riverdale
M4K
Travel
CONFIRMED
2020-03-06
2020-03-12
MALE
RESOLVED
No
No
No
46
49
NO
30 to 39 Years
Waterfront Communities-The Island
M5A
Travel
CONFIRMED
2020-03-06
2020-03-12
FEMALE
RESOLVED
No
No
No
47
50
NO
20 to 29 Years
Annex
M5R
Travel
CONFIRMED
2020-03-10
2020-03-12
MALE
RESOLVED
No
No
No
48
51
NO
30 to 39 Years
Eringate-Centennial-West Deane
M9C
Close Contact
CONFIRMED
2020-03-10
2020-03-12
FEMALE
RESOLVED
No
No
No
49
52
NO
20 to 29 Years
Palmerston-Little Italy
M6G
Close Contact
CONFIRMED
2020-03-11
2020-03-12
MALE
RESOLVED
No
No
No
50
53
NO
40 to 49 Years
Bedford Park-Nortown
M5M
Community
CONFIRMED
2020-03-06
2020-03-12
MALE
RESOLVED
No
No
No
51
54
NO
50 to 59 Years
Leaside-Bennington
M4G
Travel
CONFIRMED
2020-03-09
2020-03-12
FEMALE
RESOLVED
No
No
No
52
55
NO
50 to 59 Years
Leaside-Bennington
M4G
Travel
CONFIRMED
2020-03-08
2020-03-12
MALE
RESOLVED
No
No
No
53
56
NO
19 and younger
Leaside-Bennington
M4G
Close Contact
CONFIRMED
2020-03-11
2020-03-12
MALE
RESOLVED
No
No
No
54
57
NO
19 and younger
Leaside-Bennington
M4G
Close Contact
CONFIRMED
2020-03-12
2020-03-12
MALE
RESOLVED
No
No
No
55
58
NO
50 to 59 Years
Stonegate-Queensway
M8Y
Travel
CONFIRMED
2020-03-08
2020-03-12
MALE
RESOLVED
No
No
No
56
59
NO
20 to 29 Years
Rouge
M1C
Community
CONFIRMED
2020-03-08
2020-03-12
MALE
RESOLVED
No
No
No
57
60
NO
20 to 29 Years
Agincourt South-Malvern West
M1S
Close Contact
CONFIRMED
2020-03-07
2020-03-12
FEMALE
RESOLVED
No
No
No
58
61
NO
60 to 69 Years
Agincourt South-Malvern West
M1S
Travel
CONFIRMED
2020-03-04
2020-03-12
MALE
RESOLVED
Yes
Yes
Yes
59
62
NO
60 to 69 Years
Agincourt South-Malvern West
M1S
Travel
CONFIRMED
2020-03-05
2020-03-12
FEMALE
RESOLVED
No
No
No
60
63
NO
60 to 69 Years
Englemount-Lawrence
M6B
Community
CONFIRMED
2020-03-03
2020-03-13
MALE
RESOLVED
No
No
No
61
64
NO
30 to 39 Years
North Riverdale
M4K
Travel
CONFIRMED
2020-03-02
2020-03-13
MALE
RESOLVED
No
No
No
62
65
NO
30 to 39 Years
Roncesvalles
M6R
Travel
CONFIRMED
2020-03-09
2020-03-12
FEMALE
RESOLVED
No
No
No
63
66
NO
70 to 79 Years
Forest Hill North
M5N
Travel
CONFIRMED
2020-03-09
2020-03-13
MALE
RESOLVED
Yes
No
No
64
67
NO
20 to 29 Years
New Toronto
M8V
Travel
CONFIRMED
2020-03-12
2020-03-12
FEMALE
RESOLVED
No
No
No
65
68
NO
30 to 39 Years
West Humber-Clairville
M9W
Travel
CONFIRMED
2020-03-04
2020-03-12
MALE
RESOLVED
No
No
No
66
69
NO
20 to 29 Years
Casa Loma
M5P
Travel
CONFIRMED
2020-03-11
2020-03-12
MALE
RESOLVED
No
No
No
67
70
NO
30 to 39 Years
Annex
M4W
Travel
CONFIRMED
2020-03-09
2020-03-12
MALE
RESOLVED
No
No
No
68
71
NO
30 to 39 Years
Niagara
M5V
Community
CONFIRMED
2020-03-06
2020-03-13
FEMALE
RESOLVED
No
No
No
69
72
NO
50 to 59 Years
High Park-Swansea
M6S
Travel
CONFIRMED
2020-03-08
2020-03-13
MALE
RESOLVED
No
No
No
70
73
NO
20 to 29 Years
Waterfront Communities-The Island
M5V
Household Contact
CONFIRMED
2020-03-11
2020-03-13
FEMALE
RESOLVED
No
No
No
71
74
NO
30 to 39 Years
Downsview-Roding-CFB
M3L
Travel
CONFIRMED
2020-03-10
2020-03-13
FEMALE
RESOLVED
No
No
No
72
75
NO
40 to 49 Years
Kensington-Chinatown
M5T
Travel
CONFIRMED
2020-03-06
2020-03-13
MALE
RESOLVED
No
No
No
73
76
NO
30 to 39 Years
Waterfront Communities-The Island
M5V
Travel
CONFIRMED
2020-03-09
2020-03-13
FEMALE
RESOLVED
No
No
No
74
77
NO
30 to 39 Years
Trinity-Bellwoods
M6J
Travel
CONFIRMED
2020-03-12
2020-03-14
MALE
RESOLVED
No
No
No
75
78
NO
20 to 29 Years
Kennedy Park
M1K
Travel
PROBABLE
2020-03-10
2020-03-14
FEMALE
RESOLVED
No
No
No
76
79
NO
30 to 39 Years
Mount Pleasant East
M4S
Travel
CONFIRMED
2020-03-06
2020-03-13
FEMALE
RESOLVED
No
No
No
77
80
NO
70 to 79 Years
Victoria Village
M4A
Travel
CONFIRMED
2020-03-11
2020-03-13
MALE
FATAL
Yes
Yes
No
78
81
NO
50 to 59 Years
The Beaches
M4E
Travel
CONFIRMED
2020-03-09
2020-03-13
MALE
RESOLVED
No
No
No
79
82
NO
30 to 39 Years
Long Branch
M8W
Travel
CONFIRMED
2020-03-12
2020-03-14
MALE
RESOLVED
No
No
No
80
83
NO
40 to 49 Years
Woodbine-Lumsden
M4C
Travel
CONFIRMED
2020-03-10
2020-03-14
FEMALE
RESOLVED
No
No
No
81
84
NO
30 to 39 Years
Annex
M5R
Travel
CONFIRMED
2020-03-05
2020-03-12
MALE
RESOLVED
No
No
No
82
85
NO
60 to 69 Years
Newtonbrook East
M2M
Travel
CONFIRMED
2020-03-11
2020-03-14
MALE
RESOLVED
No
No
No
83
86
NO
20 to 29 Years
Annex
M5R
Travel
CONFIRMED
2020-03-12
2020-03-14
FEMALE
RESOLVED
No
No
No
84
87
NO
30 to 39 Years
Annex
M5R
Close Contact
PROBABLE
2020-03-09
2020-03-14
MALE
RESOLVED
No
No
No
85
88
NO
30 to 39 Years
Willowdale East
M2N
Travel
CONFIRMED
2020-03-05
2020-03-15
MALE
RESOLVED
No
No
No
86
89
NO
60 to 69 Years
L'Amoreaux
M1W
Travel
CONFIRMED
2020-03-12
2020-03-15
FEMALE
RESOLVED
No
No
No
87
90
NO
40 to 49 Years
New Toronto
M8V
Community
CONFIRMED
2020-03-12
2020-03-14
MALE
RESOLVED
No
No
No
88
91
NO
40 to 49 Years
The Beaches
M4E
Travel
CONFIRMED
2020-03-10
2020-03-15
FEMALE
RESOLVED
No
No
No
89
92
NO
30 to 39 Years
The Beaches
M4E
Travel
CONFIRMED
2020-03-09
2020-03-15
MALE
RESOLVED
No
No
No
90
93
NO
20 to 29 Years
Banbury-Don Mills
M3B
Travel
CONFIRMED
2020-03-09
2020-03-15
MALE
RESOLVED
No
No
No
91
94
NO
20 to 29 Years
Long Branch
M8V
Travel
CONFIRMED
2020-03-10
2020-03-16
MALE
RESOLVED
No
No
No
92
95
NO
19 and younger
Caledonia-Fairbank
M6E
Close Contact
PROBABLE
2020-03-12
2020-03-14
FEMALE
RESOLVED
No
No
No
93
96
NO
40 to 49 Years
Willowridge-Martingrove-Richview
M9R
Close Contact
CONFIRMED
2020-03-13
2020-03-14
FEMALE
RESOLVED
No
No
No
94
97
NO
50 to 59 Years
Yonge-St.Clair
M4V
Travel
CONFIRMED
2020-03-11
2020-03-15
FEMALE
RESOLVED
No
No
No
95
98
NO
60 to 69 Years
Bayview Woods-Steeles
M2K
Close Contact
CONFIRMED
2020-03-10
2020-03-16
FEMALE
RESOLVED
Yes
Yes
Yes
96
99
NO
50 to 59 Years
O'Connor-Parkview
M4B
Travel
CONFIRMED
2020-03-12
2020-03-15
MALE
RESOLVED
No
No
No
97
100
NO
40 to 49 Years
Woodbine-Lumsden
M4C
Travel
CONFIRMED
2020-03-16
2020-03-16
MALE
RESOLVED
No
No
No
98
101
NO
70 to 79 Years
Clairlea-Birchmount
M1K
Close Contact
CONFIRMED
2020-03-14
2020-03-16
FEMALE
RESOLVED
No
No
No
99
102
NO
70 to 79 Years
Clairlea-Birchmount
M1K
Close Contact
CONFIRMED
2020-03-15
2020-03-16
MALE
RESOLVED
No
No
No
100
103
NO
20 to 29 Years
Waterfront Communities-The Island
M5V
Travel
CONFIRMED
2020-03-13
2020-03-15
FEMALE
RESOLVED
No
No
No
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