Refactor player filtering logic in 'Manage Portfolio' to streamline beta condition application, ensuring it only processes rows that meet the alpha condition, enhancing efficiency in lineup management.

app.py

@@ -1486,6 +1486,9 @@ if selected_tab == 'Manage Portfolio':
                                 player_present = parsed_frame.apply(lambda row: player in row.values, axis=1)
                                 alpha_mask = alpha_mask & player_present
                             
+                            # Only apply beta logic to rows that match alpha condition
+                            rows_to_process = alpha_mask
+                            
                             # For rows that match alpha condition, check beta condition
                             if conditional_var == 'Any':
                                 # Check if row contains ANY of the beta players
@@ -1507,11 +1510,11 @@ if selected_tab == 'Manage Portfolio':
                                     beta_mask = beta_mask & (~player_present)
                             
                             # Combine conditions: alpha_mask AND beta_mask
-                            final_condition = alpha_mask & beta_mask
+                            final_condition = rows_to_process & beta_mask
                             
                             # Apply keep or remove logic
                             if keep_remove_var == 'Keep':
-                                parsed_frame = parsed_frame[final_condition]
+                                parsed_frame = parsed_frame[~rows_to_process | final_condition]
                             else:  # Remove
                                 parsed_frame = parsed_frame[~final_condition]
                         
@@ -1540,6 +1543,9 @@ if selected_tab == 'Manage Portfolio':
                                 player_present = parsed_frame.apply(lambda row: player in row.values, axis=1)
                                 alpha_mask = alpha_mask & player_present
                             
+                            # Only apply beta logic to rows that match alpha condition
+                            rows_to_process = alpha_mask
+                            
                             if conditional_var == 'Any':
                                 beta_mask = pd.Series([False] * len(parsed_frame), index=parsed_frame.index)
                                 for player in conditional_side_beta:
@@ -1556,10 +1562,10 @@ if selected_tab == 'Manage Portfolio':
                                     player_present = parsed_frame.apply(lambda row: player in row.values, axis=1)
                                     beta_mask = beta_mask & (~player_present)
                             
-                            final_condition = alpha_mask & beta_mask
+                            final_condition = rows_to_process & beta_mask
                             
                             if keep_remove_var == 'Keep':
-                                parsed_frame = parsed_frame[final_condition]
+                                parsed_frame = parsed_frame[~rows_to_process | final_condition]
                             else:
                                 parsed_frame = parsed_frame[~final_condition]