| import csv | |
| import datasets | |
| class GenericCSVLoader(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description="Generic CSV loader script for Hugging Face Datasets.", | |
| features=datasets.Features({ | |
| "CRASH DATE": datasets.Value("string"), | |
| "CRASH TIME": datasets.Value("string"), | |
| "BOROUGH": datasets.Value("string"), | |
| "ZIP CODE": datasets.Value("string"), | |
| "LATITUDE": datasets.Value("string"), | |
| "LONGITUDE": datasets.Value("string"), | |
| "LOCATION": datasets.Value("string"), | |
| "ON STREET NAME": datasets.Value("string"), | |
| "CROSS STREET NAME": datasets.Value("string"), | |
| "OFF STREET NAME": datasets.Value("string"), | |
| "NUMBER OF PERSONS INJURED": datasets.Value("string"), | |
| "NUMBER OF PERSONS KILLED": datasets.Value("string"), | |
| "NUMBER OF PEDESTRIANS INJURED": datasets.Value("string"), | |
| "NUMBER OF PEDESTRIANS KILLED": datasets.Value("string"), | |
| "NUMBER OF CYCLIST INJURED": datasets.Value("string"), | |
| "NUMBER OF CYCLIST KILLED": datasets.Value("string"), | |
| "NUMBER OF MOTORIST INJURED": datasets.Value("string"), | |
| "NUMBER OF MOTORIST KILLED": datasets.Value("string"), | |
| "CONTRIBUTING FACTOR VEHICLE 1": datasets.Value("string"), | |
| "CONTRIBUTING FACTOR VEHICLE 2": datasets.Value("string"), | |
| "CONTRIBUTING FACTOR VEHICLE 3": datasets.Value("string"), | |
| "CONTRIBUTING FACTOR VEHICLE 4": datasets.Value("string"), | |
| "CONTRIBUTING FACTOR VEHICLE 5": datasets.Value("string"), | |
| "COLLISION_ID": datasets.Value("string"), | |
| "VEHICLE TYPE CODE 1": datasets.Value("string"), | |
| "VEHICLE TYPE CODE 2": datasets.Value("string"), | |
| "VEHICLE TYPE CODE 3": datasets.Value("string"), | |
| "VEHICLE TYPE CODE 4": datasets.Value("string"), | |
| "VEHICLE TYPE CODE 5": datasets.Value("string") | |
| }), | |
| supervised_keys=None, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_path = dl_manager.download_and_extract("NYC_Motor_Vehicle_Collisions_Mar_12_2025.csv") | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_path}) | |
| ] | |
| def _generate_examples(self, filepath): | |
| with open(filepath, newline="", encoding="utf-8") as f: | |
| reader = csv.DictReader(f) | |
| for i, row in enumerate(reader): | |
| yield i, row | |