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