Update README.md

README.md

@@ -77,23 +77,23 @@ that were published from March until April in 1985.
 import pandas as pd
 from datetime import datetime
 
-def load_csvs_from_huggingface( start_date, end_date):
+def load_csvs_from_huggingface(start_date, end_date):
     """
     Load only the necessary CSV files from a Hugging Face dataset repository.
 
-    :param start_year: int, the start year (inclusive)
-    :param end_year: int, the end year (inclusive)
+    :param start_date: str, the start date in 'YYYY-MM-DD' format (inclusive)
+    :param end_date: str, the end date in 'YYYY-MM-DD' format (inclusive)
 
     :return: pd.DataFrame, combined data from selected CSVs
     """
-
+    huggingface_dataset_name = "amylonidis/PatClass2011"
 
     column_types = {
       "ucid": "string",
       "country": "category",
       "doc_number": "int64",
       "kind": "category",
-      "lang": "category",,
+      "lang": "category",
       "date": "int32",
       "application_date": "int32",
       "date_produced": "int32",
@@ -119,9 +119,7 @@ def load_csvs_from_huggingface( start_date, end_date):
     end_date_int = int(datetime.strptime(end_date, "%Y-%m-%d").strftime("%Y%m%d"))
 
     start_year, end_year = str(start_date_int)[:4], str(end_date_int)[:4]
-
     given_years = [str(year) for year in range(int(start_year), int(end_year) + 1)]
-
     matching_years = [f  for f in dataset_years for year in given_years if f==year]
 
     if not matching_years:
@@ -130,10 +128,9 @@ def load_csvs_from_huggingface( start_date, end_date):
     df_list = []
     for year in matching_years:
         filepath = f"data/years/{year}/clefip2011_en_classification_{year}_validated.csv"
-        print(filepath)
 
         try:
-            dataset = load_dataset("amylonidis/PatClass2011", data_files=filepath)
+            dataset = load_dataset(huggingface_dataset_name, data_files=filepath)
             df = dataset["train"].to_pandas().astype(column_types)
             df_list.append(df)
         except Exception as e:
@@ -148,6 +145,7 @@ def load_csvs_from_huggingface( start_date, end_date):
     else:
         return pd.DataFrame()
 
+
 ```
 
 ```python