Add WNBA support for contest file loading

- Implemented specific handling for WNBA lineups in the load_contest_file function, allowing for the correct parsing of player positions and lineup structure.
- Updated the DataFrame processing to accommodate WNBA-specific columns, enhancing the application's functionality for users participating in WNBA contests.

global_func/load_contest_file.py

@@ -113,6 +113,8 @@ def load_contest_file(upload, type, helper = None, sport = None):
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ', ' F ', 'F '], value=',', regex=True)
                 elif sport == 'GOLF':
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ', ' G ', 'G '], value=',', regex=True)
+                elif sport == 'WNBA':
+                    cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' F ', ' UTIL ', 'G '], value=',', regex=True)
                 print(sport)
                 check_lineups = cleaned_df.copy()
                 if sport == 'MLB':
@@ -121,6 +123,8 @@ def load_contest_file(upload, type, helper = None, sport = None):
                     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', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
+                elif sport == 'WNBA':
+                    cleaned_df[['Guard1', 'Guard2', 'Forward1', 'Forward2', 'Forward3', 'UTIL']] = 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)
@@ -130,6 +134,8 @@ def load_contest_file(upload, type, helper = None, sport = None):
                     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', 'Buddy']]
+                elif sport == 'WNBA':
+                    cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guard1', 'Guard2', 'Forward1', 'Forward2', 'Forward3', 'UTIL']]
             elif type == 'Showdown':
                 if sport == 'NHL':
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' FLEX ', 'CPT '], value=',', regex=True)