Datasets:
Update Yelpdata_663.py
Browse files- Yelpdata_663.py +39 -34
Yelpdata_663.py
CHANGED
@@ -46,17 +46,17 @@ _HOMEPAGE = "https://www.yelp.com/dataset/download"
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_LICENSE = ""
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import json
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import datasets
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class YelpDataset(datasets.GeneratorBasedBuilder):
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"""Yelp Dataset focusing on restaurant reviews."""
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="restaurants", version=VERSION, description="This part of
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]
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DEFAULT_CONFIG_NAME = "restaurants"
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@@ -70,21 +70,34 @@ class YelpDataset(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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supervised_keys=None,
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homepage="https://www.yelp.com/dataset/download",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager):
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@@ -92,20 +105,17 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
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downloaded_files = dl_manager.download_and_extract(self._URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"
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]
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def _generate_examples(self,
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"""Yields examples as (key, example) tuples."""
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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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for line in f:
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business = json.loads(line)
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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
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with open(review_path, encoding="utf-8") as f:
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@@ -113,13 +123,8 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
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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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"user_id": review['user_id'],
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"stars": review['stars'],
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"text": review['text'],
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"date": review['date'],
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}
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_LICENSE = ""
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import json
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import datasets
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from random import random
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class YelpDataset(datasets.GeneratorBasedBuilder):
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"""Yelp Dataset focusing on restaurant reviews and business information."""
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="restaurants", version=VERSION, description="This part of the dataset covers a wide range of restaurants"),
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]
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DEFAULT_CONFIG_NAME = "restaurants"
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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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"business_id": datasets.Value("string"),
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"name": datasets.Value("string"),
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"address": datasets.Value("string"),
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"city": datasets.Value("string"),
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"state": datasets.Value("string"),
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"postal_code": datasets.Value("string"),
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"latitude": datasets.Value("float"),
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"longitude": datasets.Value("float"),
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"stars_x": datasets.Value("float"),
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"review_count": datasets.Value("float"),
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"is_open": datasets.Value("float"),
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"categories": datasets.Value("string"),
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"hours": datasets.Value("string"),
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"review_id": datasets.Value("string"),
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"user_id": datasets.Value("string"),
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"stars_y": datasets.Value("float"),
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"useful": datasets.Value("float"),
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"funny": datasets.Value("float"),
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"cool": datasets.Value("float"),
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"text": datasets.Value("string"),
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"date": datasets.Value("string"),
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"attributes": datasets.Value("string"),
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}),
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supervised_keys=None,
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homepage="https://www.yelp.com/dataset/download",
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citation=_CITATION,
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license=_LICENSE,
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager):
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downloaded_files = dl_manager.download_and_extract(self._URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": downloaded_files, "split": "train"}),
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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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"""Yields examples as (key, example) tuples."""
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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 = {line['business_id']: line for line in (json.loads(line) for line in f) if "Restaurants" in line.get("categories", "")}
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# Generate examples
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with open(review_path, encoding="utf-8") as 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 = {**business, **review} # Merge business and review details
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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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