Update app.py

app.py

@@ -329,6 +329,21 @@ with tab3:
             min_sal1 = st.number_input('Min Salary', min_value = 45000, max_value = 59900, value = 59000, step = 100, key='min_sal1')
             max_sal1 = st.number_input('Max Salary', min_value = 45000, max_value = 60000, value = 60000, step = 100, key='max_sal1')
     with col2:
+        
+        with st.container():
+            if 'portfolio' in st.session_state:
+                st.dataframe(st.session_state.portfolio.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+            if 'final_outcomes_export' in st.session_state:            
+                st.download_button(
+                    label="Export Tables",
+                    data=convert_df_to_csv(st.session_state.final_outcomes_export),
+                    file_name='MLB_optimals_export.csv',
+                    mime='text/csv',
+                )
+        
+        with st.container():
+            if 'player_freq' in st.session_state:
+                st.dataframe(st.session_state.player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(expose_format, precision=2), use_container_width = True)
         if contest_var1 == 'Small Field GPP':
             if site_var1 == 'Draftkings':
                 ownframe = raw_baselines.copy()
@@ -609,7 +624,7 @@ with tab3:
                         portfolio.rename(columns={'Lineup_num': "Lineup"}, inplace = True)
                         portfolio = portfolio.set_index('Lineup')
                         portfolio = portfolio.drop(columns=['index'])
-                        portfolio = portfolio.drop_duplicates()
+                        st.session_state.portfolio = portfolio.drop_duplicates()
     
                         final_outcomes = portfolio
                         
@@ -658,6 +673,8 @@ with tab3:
                             final_outcomes_export['Own'] = final_outcomes['Own']
                             final_outcomes_export['Proj'] = final_outcomes['Proj']
                             
+                            st.session_state.final_outcomes_export = final_outcomes_export.copy()
+                            
                         elif site_var1 == 'Fanduel':
                             
                             split_portfolio[['CPT', 'CPT_ID']] = final_outcomes.CPT.str.split("-", n=1, expand = True)
@@ -686,19 +703,9 @@ with tab3:
                             final_outcomes_export['Salary'] = final_outcomes['Cost']
                             final_outcomes_export['Own'] = final_outcomes['Own']
                             final_outcomes_export['Proj'] = final_outcomes['Proj']
+                            
+                            st.session_state.final_outcomes_export = final_outcomes_export.copy()
           
-                        player_freq = player_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure']]
-                        player_freq = player_freq.set_index('Player')
-    
-                with st.container():
-                    st.dataframe(portfolio.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+                        st.session_state.player_freq = player_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure']]
     
-                st.download_button(
-                    label="Export Tables",
-                    data=convert_df_to_csv(final_outcomes),
-                    file_name='MLB_optimals_export.csv',
-                    mime='text/csv',
-                )
                 
-                with st.container():
-                    st.dataframe(player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(expose_format, precision=2), use_container_width = True)