adding diversity to analysis tables

app.py

@@ -1848,6 +1848,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
                                     })
                         else:
                             for player in player_names:
@@ -1864,6 +1865,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
                                     })
                                 
                                 # Create mask for lineups where this player is FLEX (other columns)
@@ -1881,6 +1883,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
                                     })
                     else:
                         if sport_var == 'CS2' or sport_var == 'LOL':
@@ -1899,6 +1902,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
                                     })
                                 
                                 # Create mask for lineups where this player is FLEX (other columns)
@@ -1916,6 +1920,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
                                     })
                         elif sport_var != 'CS2' and sport_var != 'LOL':
                             # Original Classic format processing
@@ -1934,6 +1939,7 @@ if selected_tab == 'Manage Portfolio':
                                         '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(),
+                                        'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
                                     })
                     
                     player_summary = pd.DataFrame(player_stats)
@@ -1952,7 +1958,8 @@ if selected_tab == 'Manage Portfolio':
                         'Avg Dupes': '{:.2f}',
                         'Avg Finish %': '{:.2%}',
                         'Avg Lineup Edge': '{:.2%}',
-                        'Exposure': '{:.2%}'
+                        'Exposure': '{:.2%}',
+                        'Avg Diversity': '{:.2%}'
                     }),
                     height=400,
                     use_container_width=True
@@ -1979,6 +1986,7 @@ if selected_tab == 'Manage Portfolio':
                                     '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(),
+                                    'Avg Diversity': st.session_state['display_frame'][stack_mask]['Diversity'].mean(),
                                 })
                         stack_summary = pd.DataFrame(stack_stats)
                         stack_summary = stack_summary.sort_values('Lineup Count', ascending=False).drop_duplicates()
@@ -1996,7 +2004,8 @@ if selected_tab == 'Manage Portfolio':
                             'Avg Dupes': '{:.2f}',
                             'Avg Finish %': '{:.2%}',
                             'Avg Lineup Edge': '{:.2%}',
-                            'Exposure': '{:.2%}'
+                            'Exposure': '{:.2%}',
+                            'Avg Diversity': '{:.2%}'
                         }),
                         height=400,
                         use_container_width=True
@@ -2034,7 +2043,8 @@ if selected_tab == 'Manage Portfolio':
                             'Avg Dupes': '{:.2f}',
                             'Avg Finish %': '{:.2%}',
                             'Avg Lineup Edge': '{:.2%}',
-                            'Exposure': '{:.2%}'
+                            'Exposure': '{:.2%}',
+                            'Diversity': '{:.2%}'
                         }),
                         height=400,
                         use_container_width=True

global_func/analyze_player_combos.py

@@ -75,8 +75,9 @@ def analyze_player_combos(display_frame, excluded_cols, combo_size=2):
             avg_dupes = display_frame.loc[combo_mask, 'Dupes'].mean()
             avg_finish = display_frame.loc[combo_mask, 'Finish_percentile'].mean()
             avg_edge = display_frame.loc[combo_mask, 'Lineup Edge'].mean()
+            avg_diversity = display_frame.loc[combo_mask, 'Diversity'].mean()
         else:
-            avg_median = avg_own = avg_dupes = avg_finish = avg_edge = 0
+            avg_median = avg_own = avg_dupes = avg_finish = avg_edge = avg_diversity = 0
         
         combo_stats.append({
             'Combo': ' + '.join(combo),
@@ -86,7 +87,8 @@ def analyze_player_combos(display_frame, excluded_cols, combo_size=2):
             'Avg Own': avg_own,
             'Avg Dupes': avg_dupes,
             'Avg Finish %': avg_finish,
-            'Avg Lineup Edge': avg_edge
+            'Avg Lineup Edge': avg_edge,
+            'Avg Diversity': avg_diversity
         })
     
     return pd.DataFrame(combo_stats)