Update Yelpdata_663.py

Yelpdata_663.py

@@ -46,17 +46,17 @@ _HOMEPAGE = "https://www.yelp.com/dataset/download"
 _LICENSE = ""
 
 
-
 import json
 import datasets
+from random import random
 
 class YelpDataset(datasets.GeneratorBasedBuilder):
-    """Yelp Dataset focusing on restaurant reviews."""
+    """Yelp Dataset focusing on restaurant reviews and business information."""
     
     VERSION = datasets.Version("1.1.0")
     
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="restaurants", version=VERSION, description="This part of my dataset covers a wide range of restaurants"),
+        datasets.BuilderConfig(name="restaurants", version=VERSION, description="This part of the dataset covers a wide range of restaurants"),
     ]
 
     DEFAULT_CONFIG_NAME = "restaurants"
@@ -70,21 +70,34 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "business_id": datasets.Value("string"),
-                    "name": datasets.Value("string"),
-                    "categories": datasets.Value("string"),
-                    "review_id": datasets.Value("string"),
-                    "user_id": datasets.Value("string"),
-                    "stars": datasets.Value("float"),
-                    "text": datasets.Value("string"),
-                    "date": datasets.Value("string"),
-                }
-            ),
+            features=datasets.Features({
+                "business_id": datasets.Value("string"),
+                "name": datasets.Value("string"),
+                "address": datasets.Value("string"),
+                "city": datasets.Value("string"),
+                "state": datasets.Value("string"),
+                "postal_code": datasets.Value("string"),
+                "latitude": datasets.Value("float"),
+                "longitude": datasets.Value("float"),
+                "stars_x": datasets.Value("float"),
+                "review_count": datasets.Value("float"),
+                "is_open": datasets.Value("float"),
+                "categories": datasets.Value("string"),
+                "hours": datasets.Value("string"),
+                "review_id": datasets.Value("string"),
+                "user_id": datasets.Value("string"),
+                "stars_y": datasets.Value("float"),
+                "useful": datasets.Value("float"),
+                "funny": datasets.Value("float"),
+                "cool": datasets.Value("float"),
+                "text": datasets.Value("string"),
+                "date": datasets.Value("string"),
+                "attributes": datasets.Value("string"),
+            }),
             supervised_keys=None,
             homepage="https://www.yelp.com/dataset/download",
             citation=_CITATION,
+            license=_LICENSE,
         )
 
     def _split_generators(self, dl_manager: datasets.DownloadManager):
@@ -92,20 +105,17 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
         downloaded_files = dl_manager.download_and_extract(self._URLS)
         
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"business_path": downloaded_files["business"], "review_path": downloaded_files["review"], "split": "train"}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"business_path": downloaded_files["business"], "review_path": downloaded_files["review"], "split": "test"}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": downloaded_files, "split": "train"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": downloaded_files, "split": "test"}),
         ]
 
-    def _generate_examples(self, business_path, review_path, split):
+    def _generate_examples(self, files, split):
         """Yields examples as (key, example) tuples."""
+        business_path, review_path = files["business"], files["review"]
         
-        # Load businesses and filter for restaurants
+        # Load businesses
         with open(business_path, encoding="utf-8") as f:
-            businesses = {}
-            for line in f:
-                business = json.loads(line)
-                if business.get("categories") and "Restaurants" in business["categories"]:
-                    businesses[business['business_id']] = business
+            businesses = {line['business_id']: line for line in (json.loads(line) for line in f) if "Restaurants" in line.get("categories", "")}
         
         # Generate examples
         with open(review_path, encoding="utf-8") as f:
@@ -113,13 +123,8 @@ class YelpDataset(datasets.GeneratorBasedBuilder):
                 review = json.loads(line)
                 business_id = review['business_id']
                 if business_id in businesses:
-                    yield review['review_id'], {
-                        "business_id": business_id,
-                        "name": businesses[business_id]['name'],
-                        "categories": businesses[business_id]['categories'],
-                        "review_id": review['review_id'],
-                        "user_id": review['user_id'],
-                        "stars": review['stars'],
-                        "text": review['text'],
-                        "date": review['date'],
-                    }
+                    business = businesses[business_id]
+                    example = {**business, **review}  # Merge business and review details
+                    # Randomly assign to split based on an 80/20 ratio
+                    if (split == 'train' and random() < 0.8) or (split == 'test' and random() >= 0.8):
+                        yield review['review_id'], example