Fixing position designations for tennis

global_func/load_contest_file.py

@@ -127,6 +127,8 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' G ', 'F ', ' F ', ' UTIL '], value=',', regex=True)
                 elif sport == 'NAS':
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' D ', 'D '], value=',', regex=True)
+                elif sport == 'TEN':
+                    cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', 'P '], value=',', regex=True)
                 elif sport == 'CFB':
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' QB ', 'QB ', ' RB ', 'RB ', 'WR ', 'WR ', ' S-FLEX ', 'S-FLEX ', ' FLEX ', 'FLEX '], value=',', regex=True)
                 print(sport)
@@ -147,6 +149,8 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
                     cleaned_df[['Remove', 'G1', 'G2', 'F1', 'F2', 'F3', 'UTIL']] = cleaned_df['Lineup'].str.split(',', expand=True)
                 elif sport == 'NAS':
                     cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
+                elif sport == 'TEN':
+                    cleaned_df[['Remove', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']] = cleaned_df['Lineup'].str.split(',', expand=True)
                 elif sport == 'CFB':
                     cleaned_df[['Remove', 'FLEX', 'QB', 'RB1', 'RB2', 'S-FLEX', 'WR1', 'WR2', 'WR3']] = cleaned_df['Lineup'].str.split(',', expand=True)
                 cleaned_df = cleaned_df.drop(columns=['Lineup', 'Remove'])
@@ -168,6 +172,8 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
                     cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'G1', 'G2', 'F1', 'F2', 'F3', 'UTIL']]
                 elif sport == 'NAS':
                     cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
+                elif sport == 'TEN':
+                    cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'Guy', 'Dude', 'Pooba', 'Bub', 'Chief', 'Buddy']]
                 elif sport == 'CFB':
                     cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'S-FLEX']]
             elif type == 'Showdown':
@@ -181,6 +187,8 @@ def load_contest_file(upload, type, helper = None, sport = None, portfolio = Non
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' G ', 'G '], value=',', regex=True)
                 elif sport == 'NAS':
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' D ', 'D '], value=',', regex=True)
+                elif sport == 'TEN':
+                    cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' P ', 'P '], value=',', regex=True)
                 else:
                     cleaned_df['Lineup'] = cleaned_df['Lineup'].replace([' UTIL ', 'CPT '], value=',', regex=True)
                 print(type)