Update app.py

app.py

@@ -512,7 +512,47 @@ with tab1:
                     file_name='MLB_consim_export.csv',
                     mime='text/csv',
                 )  
-                
+        with st.container():
+            if 'Sim_Winner_Display' in st.session_state:
+                # Create a new dataframe with summary statistics
+                summary_df = pd.DataFrame({
+                    'Metric': ['Min', 'Average', 'Max'],
+                    'Salary': [
+                        st.session_state.Sim_Winner_Display['Salary'].min(),
+                        st.session_state.Sim_Winner_Display['Salary'].mean(),
+                        st.session_state.Sim_Winner_Display['Salary'].max()
+                    ],
+                    'Proj': [
+                        st.session_state.Sim_Winner_Display['Proj'].min(),
+                        st.session_state.Sim_Winner_Display['Proj'].mean(),
+                        st.session_state.Sim_Winner_Display['Proj'].max()
+                    ],
+                    'Own': [
+                        st.session_state.Sim_Winner_Display['Own'].min(),
+                        st.session_state.Sim_Winner_Display['Own'].mean(),
+                        st.session_state.Sim_Winner_Display['Own'].max()
+                    ],
+                    'Fantasy': [
+                        st.session_state.Sim_Winner_Display['Fantasy'].min(),
+                        st.session_state.Sim_Winner_Display['Fantasy'].mean(),
+                        st.session_state.Sim_Winner_Display['Fantasy'].max()
+                    ],
+                    'GPP_Proj': [
+                        st.session_state.Sim_Winner_Display['GPP_Proj'].min(),
+                        st.session_state.Sim_Winner_Display['GPP_Proj'].mean(),
+                        st.session_state.Sim_Winner_Display['GPP_Proj'].max()
+                    ]
+                })
+
+                # Display the summary dataframe
+                st.subheader("Summary Statistics")
+                st.dataframe(summary_df.style.format({
+                    'Salary': '{:.2f}',
+                    'Proj': '{:.2f}',
+                    'Own': '{:.2%}',
+                    'Fantasy': '{:.2f}',
+                    'GPP_Proj': '{:.2f}'
+                }).background_gradient(cmap='RdYlGn', axis=0, subset=['Salary', 'Proj', 'Own', 'Fantasy', 'GPP_Proj']), use_container_width=True)
         with st.container():
             tab1, tab2, tab3, tab4, tab5, tab6, tab7, tab8, tab9 = st.tabs(['Overall Exposures', 'QB Exposures', 'RB-WR-TE Exposures', 'RB Exposures', 'WR Exposures', 'TE Exposures', 'FLEX Exposures', 'DST Exposures', 'Team Exposures'])
             with tab1: