Add more experimentation code

app/api/routers/file_upload.py

@@ -75,7 +75,7 @@ async def create_file(input_file: UploadFile, db: AsyncSession = Depends(get_db_
                         new_csv_file.close()
                 csv_file.close()
 
-                df = pd.read_csv(new_output_csv_file_path, names=['transaction_date', 'name_description', 'type', 'amount'], header=0, dtype=str, encoding='utf-8')
+                df = pd.read_csv(new_output_csv_file_path, names=['transaction_date', 'name_description', 'type', 'amount'], header=0, dtype=str, encoding='utf-8', engine='python')
                 # df = df.reindex(columns=['transaction_date', 'name_description', 'type', 'amount'])
                 # transaction_date_index = df.columns.get_loc('transaction_date')
                 result["output"] = df

app/categorization/categorizer_list.py

@@ -89,10 +89,7 @@ async def categorize_list(df: pd.DataFrame) -> pd.DataFrame:
                 # Update the category for uncategorized transactions based on the language model results
                 if not categorized_descriptions.empty:
                     # temp_df['category'] = temp_df['name_description'].map(categorized_descriptions.set_index('name_description')['category'])
-                    temp_df['name_description'] = temp_df['name_description'].astype("string")
-                    to_check = ['Amazon', 'Burger King']
-                    mask = temp_df['name_description'].isin(to_check)
-                    print(f"\ncategorize_list categorized_description not empty \nname_description: {temp_df['name_description']}\n mask: \n{temp_df[mask]}\n")
+                    print(f"\ncategorize_list current dataframe:\n {temp_df}\n")
 
                     # df['category'] = df['category'].fillna(
                     #     df['name_description'].map(