Update position lists in load_contest_file function for MMA and GOLF

- Added 'Buddy' to the position lists for both MMA and GOLF, enhancing the flexibility of player role assignments.
- Updated DataFrame structures to accommodate the new position, ensuring consistent data processing across sports.
- Maintained existing functionality while improving the application's capability to handle diverse player roles.

global_func/load_contest_file.py

@@ -5,9 +5,9 @@ def load_contest_file(upload, helper = None, sport = None):
     if sport == 'MLB':
         pos_list = [' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ']
     elif sport == 'MMA':
-        pos_list = ['Guy', 'Dude', 'Pooba', 'Bub', 'Chief']
+        pos_list = ['Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']
     elif sport == 'GOLF':
-        pos_list = ['Guy', 'Dude', 'Pooba', 'Bub', 'Chief']
+        pos_list = ['Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']
     if upload is not None:
         try:
             try:
@@ -76,18 +76,18 @@ def load_contest_file(upload, helper = None, sport = None):
             if sport == 'MLB':
                 cleaned_df[['Remove', '1B', '2B', '3B', 'C', 'OF1', 'OF2', 'OF3', 'P1', 'P2', 'SS']] = cleaned_df['Lineup'].str.split(',', expand=True)
             elif sport == 'MMA':
-                cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief']] = cleaned_df['Lineup'].str.split(',', expand=True)
+                cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
             elif sport == 'GOLF':
-                cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief']] = cleaned_df['Lineup'].str.split(',', expand=True)
+                cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
             cleaned_df = cleaned_df.drop(columns=['Lineup', 'Remove'])
             entry_counts = cleaned_df['BaseName'].value_counts()
             cleaned_df['EntryCount'] = cleaned_df['BaseName'].map(entry_counts)
             if sport == 'MLB':
                 cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'P1', 'P2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']]
             elif sport == 'MMA':
-                cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief']]
+                cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
             elif sport == 'GOLF':
-                cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief']]
+                cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
 
             print('Made it through check_lineups')