Enhance app.py by adding a new tab for Stack Type Statistics, which displays average statistics and counts for team stacks. Update existing tabs to include 'Avg Own' in dataframes and improve user feedback when simulation data is unavailable. Additionally, implement a download button for stack frequency data, enhancing data export functionality.

app.py

@@ -491,7 +491,7 @@ with tab1:
                     file_name='MLB_consim_export.csv',
                     mime='text/csv',
                 )  
-        tab1, tab2 = st.tabs(['Winning Frame Statistics', 'Flex Exposure Statistics'])
+        tab1, tab2, tab3 = st.tabs(['Winning Frame Statistics', 'Flex Exposure Statistics', 'Stack Type Statistics'])
         
         with tab1:
             if 'Sim_Winner_Display' in st.session_state:
@@ -538,6 +538,7 @@ with tab1:
                 st.dataframe(summary_df.style.format({
                     'Salary': '{:.2f}',
                     'Proj': '{:.2f}',
+                    'Own': '{:.2f}',
                     'Fantasy': '{:.2f}',
                     'GPP_Proj': '{:.2f}'
                 }).background_gradient(cmap='RdYlGn', axis=0, subset=['Salary', 'Proj', 'Own', 'Fantasy', 'GPP_Proj']), use_container_width=True)
@@ -569,14 +570,47 @@ with tab1:
                 st.dataframe(flex_summary.style.format({
                     'Count': '{:.0f}',
                     'Avg Proj': '{:.2f}',
+                    'Avg Own': '{:.2f}',
                     'Avg Fantasy': '{:.2f}',
                     'Avg GPP_Proj': '{:.2f}'
                 }).background_gradient(cmap='RdYlGn', axis=0, subset=['Count', 'Avg Proj', 'Avg Own', 'Avg Fantasy', 'Avg GPP_Proj']), use_container_width=True)
+            else:
+                st.write("Simulation data or position mapping not available.")
+
+        with tab3:
+            if 'Sim_Winner_Display' in st.session_state:
+                # Apply position mapping to FLEX column
+                stack_counts = st.session_state.freq_copy['Team_count'].value_counts()
+                
+                # Calculate average statistics for each stack size
+                stack_stats = st.session_state.freq_copy.groupby('Team_count').agg({
+                    'proj': 'mean',
+                    'Own': 'mean',
+                    'Fantasy': 'mean',
+                    'GPP_Proj': 'mean'
+                })
                 
+                # Combine counts and average statistics
+                stack_summary = pd.concat([stack_counts, stack_stats], axis=1)
+                stack_summary.columns = ['Count', 'Avg Proj', 'Avg Own', 'Avg Fantasy', 'Avg GPP_Proj']
+                stack_summary = stack_summary.reset_index()
+                stack_summary.columns = ['Position', 'Count', 'Avg Proj', 'Avg Own', 'Avg Fantasy', 'Avg GPP_Proj']
+                
+                # Display the summary dataframe
+                st.subheader("Stack Type Statistics")
+                st.dataframe(stack_summary.style.format({
+                    'Count': '{:.0f}',
+                    'Avg Proj': '{:.2f}',
+                    'Avg Own': '{:.2f}',
+                    'Avg Fantasy': '{:.2f}',
+                    'Avg GPP_Proj': '{:.2f}'
+                }).background_gradient(cmap='RdYlGn', axis=0, subset=['Count', 'Avg Proj', 'Avg Own', 'Avg Fantasy', 'Avg GPP_Proj']), use_container_width=True)
             else:
                 st.write("Simulation data or position mapping not available.")
+                
+            
         with st.container():
-            tab1, tab2, tab3, tab4, tab5, tab6, tab7 = st.tabs(['Overall Exposures', 'Center Exposures', 'Wing Exposures', 'Defense Exposures', 'Flex Exposures', 'Goalie Exposures', 'Team Exposures'])
+            tab1, tab2, tab3, tab4, tab5, tab6, tab7, tab8 = st.tabs(['Overall Exposures', 'Center Exposures', 'Wing Exposures', 'Defense Exposures', 'Flex Exposures', 'Goalie Exposures', 'Team Exposures', 'Stack Exposures'])
             with tab1:
                 if 'player_freq' in st.session_state:
                     
@@ -653,4 +687,15 @@ with tab1:
                         file_name='team_freq.csv',
                         mime='text/csv',
                         key='team'
+                    )
+            with tab8:
+                if 'stack_freq' in st.session_state:
+                    
+                    st.dataframe(st.session_state.stack_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
+                    st.download_button(
+                        label="Export Exposures",
+                        data=st.session_state.stack_freq.to_csv().encode('utf-8'),
+                        file_name='stack_freq.csv',
+                        mime='text/csv',
+                        key='team'
                     )