Refactor player filtering logic in app.py to consolidate mask creation for including and removing players. This change enhances code readability and maintains the functionality of dynamic player selection based on user-defined criteria.

app.py

@@ -1318,21 +1318,14 @@ with tab2:
 
                         # Get player columns (excluding non-player columns)
                         player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
-                        
-                        # Create masks similar to lines 1205-1211
-                        if conditional_include_players:
-                            include_mask = parsed_frame[player_columns].apply(
-                                lambda row: all(player in list(row) for player in conditional_include_players), axis=1
-                            )
-                        else:
-                            include_mask = pd.Series([True] * len(parsed_frame))
+
+                        include_mask = parsed_frame[player_columns].apply(
+                            lambda row: all(player in list(row) for player in conditional_include_players), axis=1
+                        )
                             
-                        if conditional_remove_players:
-                            remove_mask = parsed_frame[player_columns].apply(
-                                lambda row: not any(player in list(row) for player in conditional_remove_players), axis=1
-                            )
-                        else:
-                            remove_mask = pd.Series([True] * len(parsed_frame))
+                        remove_mask = parsed_frame[player_columns].apply(
+                            lambda row: all(player in list(row) for player in conditional_remove_players), axis=1
+                        )
                             
                         parsed_frame = parsed_frame[include_mask & remove_mask]
 
@@ -1345,20 +1338,13 @@ with tab2:
                         # Get player columns (excluding non-player columns)
                         player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
                         
-                        # Create masks similar to lines 1205-1211
-                        if conditional_include_players:
-                            include_mask = parsed_frame[player_columns].apply(
-                                lambda row: all(player in list(row) for player in conditional_include_players), axis=1
-                            )
-                        else:
-                            include_mask = pd.Series([True] * len(parsed_frame))
-                            
-                        if conditional_remove_players:
-                            remove_mask = parsed_frame[player_columns].apply(
-                                lambda row: not any(player in list(row) for player in conditional_remove_players), axis=1
-                            )
-                        else:
-                            remove_mask = pd.Series([True] * len(parsed_frame))
+                        include_mask = parsed_frame[player_columns].apply(
+                            lambda row: all(player in list(row) for player in conditional_include_players), axis=1
+                        )
+                        
+                        remove_mask = parsed_frame[player_columns].apply(
+                            lambda row: all(player in list(row) for player in conditional_remove_players), axis=1
+                        )
                             
                         parsed_frame = parsed_frame[include_mask & remove_mask]