Datasets:

blinoff
/

medical_institutions_reviews

	import datasets
	import json

	class HfreviewsConfig(datasets.BuilderConfig):
	def __init__(self, features, **kwargs):
	super(HfreviewsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
	self.features = features

	class MedicalInstitutionsReviews(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	HfreviewsConfig(
	name="simple",
	description="Simple config",
	features=["review_id", "content", "general", "quality", "service", "equipment", "food", "location"],
	)
	]

	def _info(self):
	return datasets.DatasetInfo(
	description='Healthcare facilities reviews dataset.',
	features=datasets.Features(
	{
	"review_id": datasets.Value("string"),
	"content": datasets.Value("string"),
	"general": datasets.Value("string"),
	"quality": datasets.Value("string"),
	"service": datasets.Value("string"),
	"equipment": datasets.Value("string"),
	"food": datasets.Value("string"),
	"location": datasets.Value("string"),
	"Idx": datasets.Value("int32"),
	}
	),
	)

	def _split_generators(self, dl_manager: datasets.DownloadManager):
	urls_to_download = {
	"train": "medical_institutions_reviews.jsonl"
	}
	downloaded_files = dl_manager.download_and_extract(urls_to_download)

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]})
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	for uid, row in enumerate(f):
	data = json.loads(row)
	data["Idx"] = uid
	yield uid, data