Update clefip2011.py

clefip2011.py

@@ -15,19 +15,17 @@ class CLEFIP2011(datasets.GeneratorBasedBuilder):
     """Custom Dataset Loader"""
 
     BUILDER_CONFIG_CLASS = CLEFIP2011Config
-    
+
     BUILDER_CONFIGS = [
         CLEFIP2011Config(
             name="bibliographic",
             version=datasets.Version("1.0.0"),
             description="CLEF-IP 2011 Bibliographic Data",
-            data_url="https://huggingface.co/datasets/amylonidis/PatClass2011/resolve/main/clefip2011_bibliographic_clean.tar.gz",
             dataset_type="bibliographic",
         ),
     ]
 
     def _info(self):
-
         if self.config.dataset_type == "bibliographic":
             features = datasets.Features(
                 {
@@ -65,13 +63,16 @@ class CLEFIP2011(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-
         archive_path = dl_manager.download_and_extract(
             "https://huggingface.co/datasets/amylonidis/PatClass2011/resolve/main/clefip2011_bibliographic_clean.tar.gz"
         )
 
         bibliographic_file = os.path.join(archive_path, "clefip2011_bibliographic.csv")
 
+        # Check if the file exists
+        if not os.path.isfile(bibliographic_file):
+            raise FileNotFoundError(f"{bibliographic_file} not found in the extracted archive.")
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -83,11 +84,8 @@ class CLEFIP2011(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, filepaths, split):
-
         for filepath in filepaths:
-            df = pd.read_csv(filepath, header=None)
-
-            column_names = [
+            df = pd.read_csv(filepath, names=[
                 "ucid",
                 "country",
                 "doc_number",
@@ -113,14 +111,10 @@ class CLEFIP2011(datasets.GeneratorBasedBuilder):
                 "claims_de_exist",
                 "claims_fr_exist",
                 "claims_en_exist",
-            ]
-            df.columns = column_names
+            ], header=None)
 
             df["date"] = pd.to_datetime(df["date"], format="%Y%m%d").astype(str)
-
-            df["date_produced"] = pd.to_datetime(
-                df["date_produced"], format="%Y%m%d"
-            ).astype(str)
+            df["date_produced"] = pd.to_datetime(df["date_produced"], format="%Y%m%d").astype(str)
 
             boolean_columns = [
                 "abstract_de_exist",
@@ -136,5 +130,6 @@ class CLEFIP2011(datasets.GeneratorBasedBuilder):
             for col in boolean_columns:
                 df[col] = df[col].astype(bool)
 
-            for idx, row in df.iterrows():
-                yield idx, row.to_dict()
+            for idx, row in enumerate(df.to_dict(orient="records")):
+                yield idx, row
+