Refactor helper DataFrame selection in load_contest_file function

- Simplified the DataFrame selection by retaining only essential columns: 'Player', 'Salary', and 'Team'.
- Removed unnecessary processing steps related to entry names and ownership percentages, streamlining the data loading process.
- Maintained existing functionality while improving code clarity and efficiency.

global_func/load_contest_file.py

@@ -45,19 +45,7 @@ def load_contest_file(upload, helper = None, sport = None):
             
             # Select and rename essential columns for the actual upload
             if helper is not None:
-                df_helper = helper_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS', 'Salary', 'Team']]
-                df_helper = df_helper.rename(columns={'Roster Position': 'Pos', '%Drafted': 'Own'})
-                
-                # Split EntryName into base name and entry count
-                df_helper['BaseName'] = df_helper['EntryName'].str.replace(r'\s*\(\d+/\d+\)$', '', regex=True)
-                df_helper['EntryCount'] = df_helper['EntryName'].str.extract(r'\((\d+/\d+)\)')
-                df_helper['EntryCount'] = df_helper['EntryCount'].fillna('1/1')  # Default to 1/1 if no entry count
-                
-                # Convert ownership percentage to float
-                try:
-                    df_helper['Own'] = df_helper['Own'].str.replace('%', '').astype(float)
-                except:
-                    df_helper['Own'] = df_helper['Own'].astype(float)
+                df_helper = helper_df[['Player', 'Salary', 'Team']]
             
             print('Made it through helper')