Refactor display frame handling in app.py to use a unified session state variable. Update references to 'display_frame' to ensure consistency and improve data management across various functionalities, including player and stack analysis.

app.py

@@ -1263,15 +1263,15 @@ with tab2:
             
             display_frame_source = st.selectbox("Display:", options=['Portfolio', 'Export Base'], key='display_frame_source')
             if display_frame_source == 'Portfolio':
-                display_frame = st.session_state['working_frame']
-                st.session_state['export_file'] = display_frame.copy()
+                st.session_state['display_frame'] = st.session_state['working_frame']
+                st.session_state['export_file'] = st.session_state['display_frame'].copy()
                 
                 for col in st.session_state['export_file'].columns:
                     if col not in excluded_cols:
                         st.session_state['export_file'][col] = st.session_state['export_file'][col].map(st.session_state['export_dict'])
             elif display_frame_source == 'Export Base':
-                display_frame = st.session_state['export_base']
-                st.session_state['export_file'] = display_frame.copy()
+                st.session_state['display_frame'] = st.session_state['export_base']
+                st.session_state['export_file'] = st.session_state['display_frame'].copy()
                 
                 for col in st.session_state['export_file'].columns:
                     if col not in excluded_cols:
@@ -1297,11 +1297,11 @@ with tab2:
                     if st.button("Clear Custom Export"):
                         st.session_state['export_base'] = pd.DataFrame(columns=st.session_state['working_frame'].columns)
                         if display_frame_source == 'Portfolio':
-                            display_frame = st.session_state['working_frame']
+                            st.session_state['display_frame'] = st.session_state['working_frame']
                         elif display_frame_source == 'Export Base':
-                            display_frame = st.session_state['export_base']
+                            st.session_state['display_frame'] = st.session_state['export_base']
 
-            total_rows = len(display_frame)
+            total_rows = len(st.session_state['display_frame'])
             rows_per_page = 100
             total_pages = (total_rows + rows_per_page - 1) // rows_per_page  # Ceiling division
 
@@ -1328,7 +1328,7 @@ with tab2:
             end_idx = min(start_idx + rows_per_page, total_rows)
 
             # Get the subset of data for the current page
-            current_page_data = display_frame.iloc[start_idx:end_idx]
+            current_page_data = st.session_state['display_frame'].iloc[start_idx:end_idx]
             # Display the paginated dataframe first
             st.dataframe(
                 current_page_data.style
@@ -1367,7 +1367,7 @@ with tab2:
         with player_stats_col:
             if st.button("Analyze Players", key='analyze_players'):
                 player_stats = []
-                player_columns = [col for col in display_frame.columns if col not in excluded_cols]
+                player_columns = [col for col in st.session_state['display_frame'].columns if col not in excluded_cols]
                 
                 if st.session_state['settings_base'] and 'origin_player_exposures' in st.session_state and display_frame_source == 'Portfolio':
                     st.session_state['player_summary'] = st.session_state['origin_player_exposures']
@@ -1375,7 +1375,7 @@ with tab2:
                     if type_var == 'Showdown':
                         if sport_var == 'GOLF':
                             for player in player_names:
-                                player_mask = display_frame[player_columns].apply(
+                                player_mask = st.session_state['display_frame'][player_columns].apply(
                                     lambda row: player in list(row), axis=1
                                 )
                                 
@@ -1383,32 +1383,32 @@ with tab2:
                                     player_stats.append({
                                         'Player': player,
                                         'Lineup Count': player_mask.sum(),
-                                        'Exposure': player_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[player_mask]['median'].mean(),
-                                        'Avg Own': display_frame[player_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[player_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[player_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[player_mask]['Lineup Edge'].mean(),
+                                        'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
                                     })
                         else:
                             for player in player_names:
                                 # Create mask for lineups where this player is Captain (first column)
-                                cpt_mask = display_frame[player_columns[0]] == player
+                                cpt_mask = st.session_state['display_frame'][player_columns[0]] == player
                                 
                                 if cpt_mask.any():
                                     player_stats.append({
                                         'Player': f"{player} (CPT)",
                                         'Lineup Count': cpt_mask.sum(),
-                                        'Exposure': cpt_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[cpt_mask]['median'].mean(),
-                                        'Avg Own': display_frame[cpt_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[cpt_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[cpt_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[cpt_mask]['Lineup Edge'].mean(),
+                                        'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
                                     })
                                 
                                 # Create mask for lineups where this player is FLEX (other columns)
-                                flex_mask = display_frame[player_columns[1:]].apply(
+                                flex_mask = st.session_state['display_frame'][player_columns[1:]].apply(
                                     lambda row: player in list(row), axis=1
                                 )
                                 
@@ -1416,34 +1416,34 @@ with tab2:
                                     player_stats.append({
                                         'Player': f"{player} (FLEX)",
                                         'Lineup Count': flex_mask.sum(),
-                                        'Exposure': flex_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[flex_mask]['median'].mean(),
-                                        'Avg Own': display_frame[flex_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[flex_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[flex_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[flex_mask]['Lineup Edge'].mean(),
+                                        'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
                                     })
                     else:
                         if sport_var == 'CS2' or sport_var == 'LOL':
                             # Handle Captain positions
                             for player in player_names:
                                 # Create mask for lineups where this player is Captain (first column)
-                                cpt_mask = display_frame[player_columns[0]] == player
+                                cpt_mask = st.session_state['display_frame'][player_columns[0]] == player
                                 
                                 if cpt_mask.any():
                                     player_stats.append({
                                         'Player': f"{player} (CPT)",
                                         'Lineup Count': cpt_mask.sum(),
-                                        'Exposure': cpt_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[cpt_mask]['median'].mean(),
-                                        'Avg Own': display_frame[cpt_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[cpt_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[cpt_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[cpt_mask]['Lineup Edge'].mean(),
+                                        'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
                                     })
                                 
                                 # Create mask for lineups where this player is FLEX (other columns)
-                                flex_mask = display_frame[player_columns[1:]].apply(
+                                flex_mask = st.session_state['display_frame'][player_columns[1:]].apply(
                                     lambda row: player in list(row), axis=1
                                 )
                                 
@@ -1451,17 +1451,17 @@ with tab2:
                                     player_stats.append({
                                         'Player': f"{player} (FLEX)",
                                         'Lineup Count': flex_mask.sum(),
-                                        'Exposure': flex_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[flex_mask]['median'].mean(),
-                                        'Avg Own': display_frame[flex_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[flex_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[flex_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[flex_mask]['Lineup Edge'].mean(),
+                                        'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
                                     })
                         elif sport_var != 'CS2' and sport_var != 'LOL':
                             # Original Classic format processing
                             for player in player_names:
-                                player_mask = display_frame[player_columns].apply(
+                                player_mask = st.session_state['display_frame'][player_columns].apply(
                                     lambda row: player in list(row), axis=1
                                 )
                                 
@@ -1469,12 +1469,12 @@ with tab2:
                                     player_stats.append({
                                         'Player': player,
                                         'Lineup Count': player_mask.sum(),
-                                        'Exposure': player_mask.sum() / len(display_frame),
-                                        'Avg Median': display_frame[player_mask]['median'].mean(),
-                                        'Avg Own': display_frame[player_mask]['Own'].mean(),
-                                        'Avg Dupes': display_frame[player_mask]['Dupes'].mean(),
-                                        'Avg Finish %': display_frame[player_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': display_frame[player_mask]['Lineup Edge'].mean(),
+                                        'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
+                                        'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
+                                        'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
+                                        'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
+                                        'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
+                                        'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
                                     })
                     
                     player_summary = pd.DataFrame(player_stats)
@@ -1500,26 +1500,26 @@ with tab2:
                 )
         
         with stack_stats_col:
-            if 'Stack' in display_frame.columns:
+            if 'Stack' in st.session_state['display_frame'].columns:
                 if st.button("Analyze Stacks", key='analyze_stacks'):
                     stack_stats = []
-                    stack_columns = [col for col in display_frame.columns if col.startswith('Stack')]
+                    stack_columns = [col for col in st.session_state['display_frame'].columns if col.startswith('Stack')]
 
                     if st.session_state['settings_base'] and 'origin_stack_exposures' in st.session_state and display_frame_source == 'Portfolio':
                         st.session_state['stack_summary'] = st.session_state['origin_stack_exposures']
                     else:
                         for stack in st.session_state['stack_dict'].values():
-                            stack_mask = display_frame['Stack'] == stack
+                            stack_mask = st.session_state['display_frame']['Stack'] == stack
                             if stack_mask.any():
                                 stack_stats.append({
                                     'Stack': stack,
                                     'Lineup Count': stack_mask.sum(),
-                                    'Exposure': stack_mask.sum() / len(display_frame),
-                                    'Avg Median': display_frame[stack_mask]['median'].mean(),
-                                    'Avg Own': display_frame[stack_mask]['Own'].mean(),
-                                    'Avg Dupes': display_frame[stack_mask]['Dupes'].mean(),
-                                    'Avg Finish %': display_frame[stack_mask]['Finish_percentile'].mean(),
-                                    'Avg Lineup Edge': display_frame[stack_mask]['Lineup Edge'].mean(),
+                                    'Exposure': stack_mask.sum() / len(st.session_state['display_frame']),
+                                    'Avg Median': st.session_state['display_frame'][stack_mask]['median'].mean(),
+                                    'Avg Own': st.session_state['display_frame'][stack_mask]['Own'].mean(),
+                                    'Avg Dupes': st.session_state['display_frame'][stack_mask]['Dupes'].mean(),
+                                    'Avg Finish %': st.session_state['display_frame'][stack_mask]['Finish_percentile'].mean(),
+                                    'Avg Lineup Edge': st.session_state['display_frame'][stack_mask]['Lineup Edge'].mean(),
                                 })
                         stack_summary = pd.DataFrame(stack_stats)
                         stack_summary = stack_summary.sort_values('Lineup Count', ascending=False).drop_duplicates()
@@ -1555,7 +1555,7 @@ with tab2:
                 with col2:
                     if st.button("Analyze Combos", key='analyze_combos'):
                         st.session_state['combo_analysis'] = analyze_player_combos(
-                            display_frame, excluded_cols, combo_size
+                            st.session_state['display_frame'], excluded_cols, combo_size
                         )
                 
                 # Display results