Create NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.py

NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.py

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+import json
+import os
+from typing import List
+import pandas as pd
+import datasets
+import boto3
+from botocore import UNSIGNED
+from botocore.config import Config
+
+
+_CITATION = """\
+@misc{ny_motor_vehicle_collisions_weather_dataset,
+  title={New York City Motor Vehicle Collisions and Weather Dataset},
+  author={XX103},
+  year={2024},
+  url={https://huggingface.co/datasets/xx103/NYC_Motor_Vehicle_Collisions_and_Weather_Dataset},
+}
+"""
+
+_DESCRIPTION = """\
+This dataset contains information about motor vehicle collisions in New York City, along with associated weather conditions. 
+Each record includes details about the crash date, location, collision ID, crash time period, contributing factors, vehicle types, 
+the number of injuries and deaths, street name, weather description, and temperature metrics.
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/xx103/NYC_Motor_Vehicle_Collisions_and_Weather_Dataset"
+
+_LICENSE = "Apache License 2.0"
+
+class NYCMotorVehicleCollisionsWeatherDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    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"),
+                }
+            ),
+            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))
+        bucket_name = 'sta663data1'
+        file_key = 'NYC_Motor_Vehicle_Collisions_and_Weather_Dataset.json'
+        local_file_name = dl_manager.download(f"s3://{bucket_name}/{file_key}")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": local_file_name,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            for key, row in enumerate(data):
+                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"],
+                }