Update app.py

app.py

@@ -1267,7 +1267,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         player_freq['Team'] = player_freq['Team'].replace(item_list, team_list)
     
-                    player_freq = player_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.player_freq = player_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     qb_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,0:1].values, return_counts=True)),
                                                 columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1281,7 +1281,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         qb_freq['Team'] = qb_freq['Team'].replace(item_list, team_list)
     
-                    qb_freq = qb_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.qb_freq = qb_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
     
                     rb_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,[1, 2]].values, return_counts=True)),
                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1295,7 +1295,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         rb_freq['Team'] = rb_freq['Team'].replace(item_list, team_list)
     
-                    rb_freq = rb_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.rb_freq = rb_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     wr_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,[3, 4, 5]].values, return_counts=True)),
                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1309,7 +1309,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         wr_freq['Team'] = wr_freq['Team'].replace(item_list, team_list)
     
-                    wr_freq = wr_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.wr_freq = wr_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     te_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,[6]].values, return_counts=True)),
                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1323,7 +1323,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         te_freq['Team'] = te_freq['Team'].replace(item_list, team_list)
     
-                    te_freq = te_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.te_freq = te_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     flex_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,[7]].values, return_counts=True)),
                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1337,7 +1337,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         flex_freq['Team'] = flex_freq['Team'].replace(item_list, team_list)
     
-                    flex_freq = flex_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.flex_freq = flex_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     dst_freq = pd.DataFrame(np.column_stack(np.unique(Sim_Winner_Frame.iloc[:,8:9].values, return_counts=True)),
                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1351,7 +1351,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         dst_freq['Team'] = dst_freq['Team'].replace(item_list, team_list)
     
-                    dst_freq = dst_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.dst_freq = dst_freq[['Player', 'Team', 'Position', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                 
         with st.container():
             simulate_container = st.empty()
@@ -1378,7 +1378,7 @@ with tab2:
             freq_container = st.empty()
             tab1, tab2, tab3, tab4, tab5, tab6, tab7 = st.tabs(['Overall Exposures', 'QB Exposures', 'RB Exposures', 'WR Exposures', 'TE Exposures', 'FLEX Exposures', 'DST Exposures'])
             with tab1:
-                st.dataframe(player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.player_freq),
@@ -1386,7 +1386,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab2:
-                st.dataframe(qb_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.qb_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.qb_freq),
@@ -1394,7 +1394,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab3:
-                st.dataframe(rb_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.rb_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.rb_freq),
@@ -1402,7 +1402,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab4:
-                st.dataframe(wr_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.wr_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.wr_freq),
@@ -1410,7 +1410,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab5:
-                st.dataframe(te_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.te_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.te_freq),
@@ -1418,7 +1418,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab6:
-                st.dataframe(flex_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.flex_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.flex_freq),
@@ -1426,7 +1426,7 @@ with tab2:
                     mime='text/csv',
                 )
             with tab7:
-                st.dataframe(dst_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
+                st.dataframe(st.session_state.dst_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
                 st.download_button(
                     label="Export Exposures",
                     data=convert_df_to_csv(st.session_state.dst_freq),