Update NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.py

NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.py

@@ -1,13 +1,9 @@
 import json
 import os
-from typing import List
-import pandas as pd
+import tempfile
 import datasets
 import boto3
-from botocore import UNSIGNED
 from botocore.config import Config
-import tempfile
-
 
 _CITATION = """\
 @misc{ny_motor_vehicle_collisions_weather_dataset,
@@ -34,76 +30,68 @@ class NYCMotorVehicleCollisionsWeatherDataset(datasets.GeneratorBasedBuilder):
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "crash_date": datasets.Value("string"),
-                    "borough": datasets.Value("string"),
-                    "zip_code": datasets.Value("string"),
-                    "latitude": datasets.Value("float"),
-                    "longitude": datasets.Value("float"),
-                    "collision_id": datasets.Value("int32"),
-                    "crash_time_period": datasets.Value("string"),
-                    "contributing_factor_vehicles": datasets.Sequence(datasets.Value("string")),
-                    "vehicle_types": datasets.Sequence(datasets.Value("string")),
-                    "number_of_injuries": datasets.Value("int32"),
-                    "number_of_deaths": datasets.Value("int32"),
-                    "street_name": datasets.Value("string"),
-                    "street_type": datasets.Value("string"),
-                    "weather_description": datasets.Value("string"),
-                    "precipitation": datasets.Value("float"),
-                    "precipitation_type": datasets.Value("string"),
-                    "temp_max": datasets.Value("float"),
-                    "temp_min": datasets.Value("float"),
-                }
-            ),
+            features=datasets.Features({
+                "crash_date": datasets.Value("string"),
+                "borough": datasets.Value("string"),
+                "zip_code": datasets.Value("string"),
+                "latitude": datasets.Value("float"),
+                "longitude": datasets.Value("float"),
+                "collision_id": datasets.Value("int32"),
+                "crash_time_period": datasets.Value("string"),
+                "contributing_factor_vehicles": datasets.Sequence(datasets.Value("string")),
+                "vehicle_types": datasets.Sequence(datasets.Value("string")),
+                "number_of_injuries": datasets.Value("int32"),
+                "number_of_deaths": datasets.Value("int32"),
+                "street_name": datasets.Value("string"),
+                "street_type": datasets.Value("string"),
+                "weather_description": datasets.Value("string"),
+                "precipitation": datasets.Value("float"),
+                "precipitation_type": datasets.Value("string"),
+                "temp_max": datasets.Value("float"),
+                "temp_min": datasets.Value("float"),
+            }),
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
-        # Initialize the S3 client for anonymous access
-        s3 = boto3.client('s3', config=Config(signature_version=UNSIGNED))
+        s3 = boto3.client('s3', config=Config(signature_version='s3v4'))
         bucket_name = 'sta663data1'
         file_key = 'NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.json'
         
-        # Create a temporary file to download the dataset to
         local_file_name = os.path.join(tempfile.gettempdir(), file_key)
-        
-        # Download the file from S3
         s3.download_file(bucket_name, file_key, local_file_name)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": local_file_name,
-                    "split": "train",
-                },
+                gen_kwargs={"filepath": local_file_name},
             ),
         ]
-                }
-    def _generate_examples(self, filepath, split):
+
+    def _generate_examples(self, filepath):
         with open(filepath, encoding="utf-8") as f:
-            for key, line in enumerate(f):
-                row = json.loads(line)  
-                    yield key, {
-                    "crash_date": row["crash_date"],
-                    "borough": row["borough"],
-                    "zip_code": row["zip_code"],
-                    "latitude": row["latitude"],
-                    "longitude": row["longitude"],
-                    "collision_id": row["collision_id"],
-                    "crash_time_period": row["crash_time_period"],
-                    "contributing_factor_vehicles": row["contributing_factor_vehicles"],
-                    "vehicle_types": row["vehicle_types"],
-                    "number_of_injuries": row["number_of_injuries"],
-                    "number_of_deaths": row["number_of_deaths"],
-                    "street_name": row["street_name"],
-                    "street_type": row["street_type"],
-                    "weather_description": row["weather_description"],
-                    "precipitation": row["precipitation"],
-                    "precipitation_type": row["precipitation_type"],
-                    "temp_max": row["temp_max"],
-                    "temp_min": row["temp_min"],
+            # Adjusted to handle a standard JSON array file
+            data = json.load(f)
+            for key, row in enumerate(data):
+                yield key, {
+                    "crash_date": row.get("crash_date", ""),
+                    "borough": row.get("borough", ""),
+                    "zip_code": row.get("zip_code", ""),
+                    "latitude": row.get("latitude", None),
+                    "longitude": row.get("longitude", None),
+                    "collision_id": row.get("collision_id", None),
+                    "crash_time_period": row.get("crash_time_period", ""),
+                    "contributing_factor_vehicles": row.get("contributing_factor_vehicles", []),
+                    "vehicle_types": row.get("vehicle_types", []),
+                    "number_of_injuries": row.get("number_of_injuries", None),
+                    "number_of_deaths": row.get("number_of_deaths", None),
+                    "street_name": row.get("street_name", ""),
+                    "street_type": row.get("street_type", ""),
+                    "weather_description": row.get("weather_description", ""),
+                    "precipitation": row.get("precipitation", None),
+                    "precipitation_type": row.get("precipitation_type", ""),
+                    "temp_max": row.get("temp_max", None),
+                    "temp_min": row.get("temp_min", None),
                 }