Datasets:
Update Yelpdata_663.py
Browse files- Yelpdata_663.py +37 -8
Yelpdata_663.py
CHANGED
@@ -109,22 +109,51 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": downloaded_files, "split": "test"}),
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]
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def _generate_examples(self, files, split):
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business_path, review_path = files["business"], files["review"]
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# Load businesses
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with open(business_path, encoding="utf-8") as f:
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businesses = {
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with open(review_path, encoding="utf-8") as f:
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for line in f:
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review = json.loads(line)
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business_id = review['business_id']
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if business_id in businesses:
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business = businesses[business_id]
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example = {
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if (split == 'train' and random() < 0.8) or (split == 'test' and random() >= 0.8):
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yield review['review_id'], example
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": downloaded_files, "split": "test"}),
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]
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+
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def _generate_examples(self, files, split):
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"""Yields examples as (key, example) tuples."""
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business_path, review_path = files["business"], files["review"]
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# Load businesses and filter for restaurants
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with open(business_path, encoding="utf-8") as f:
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businesses = {}
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for line in f:
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business = json.loads(line)
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# Check if 'categories' is not None and contains "Restaurants"
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if business.get("categories") and "Restaurants" in business["categories"]:
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businesses[business['business_id']] = business
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# Generate examples with an attempted 80/20 split for train/test
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with open(review_path, encoding="utf-8") as f:
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for line in f:
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review = json.loads(line)
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business_id = review['business_id']
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if business_id in businesses:
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business = businesses[business_id]
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example = {
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"business_id": business['business_id'],
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"name": business.get("name", ""),
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"address": business.get("address", ""),
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"city": business.get("city", ""),
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"state": business.get("state", ""),
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"postal_code": business.get("postal_code", ""),
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"latitude": business.get("latitude", None),
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"longitude": business.get("longitude", None),
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"stars_x": business.get("stars", None),
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"review_count": business.get("review_count", None),
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"is_open": business.get("is_open", None),
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"categories": business.get("categories", ""),
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"hours": json.dumps(business.get("hours", {})), # Storing hours as a JSON string
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"review_id": review.get("review_id", ""),
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"user_id": review.get("user_id", ""),
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"stars_y": review.get("stars", None),
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"useful": review.get("useful", None),
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"funny": review.get("funny", None),
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"cool": review.get("cool", None),
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"text": review.get("text", ""),
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"date": review.get("date", ""),
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"attributes": json.dumps(business.get("attributes", {})), # Storing attributes as a JSON string
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}
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# Randomly assign to split based on an 80/20 ratio
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if (split == 'train' and random() < 0.8) or (split == 'test' and random() >= 0.8):
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yield review['review_id'], example
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