Update app.py

app.py

@@ -753,7 +753,7 @@ with tab2:
             scaling_var = 15
             
     with col2:
-        with st.container():
+        with st.conatainer():
             if st.button("Simulate Contest", key='sim1'):
                 try:
                     del dst_freq
@@ -1055,7 +1055,7 @@ 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']]
                     
                     cpt_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Frame.iloc[:,0:1].values, return_counts=True)),
                                                 columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1069,7 +1069,7 @@ with tab2:
                     for checkVar in range(len(team_list)):
                                         cpt_freq['Team'] = cpt_freq['Team'].replace(item_list, team_list)
     
-                    cpt_freq = cpt_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.cpt_freq = cpt_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     flex_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Frame.iloc[:,[1, 2, 3, 4, 5]].values, return_counts=True)),
                                                 columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
@@ -1083,7 +1083,7 @@ 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', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
+                    st.session_state.flex_freq = flex_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure', 'Edge']]
                     
                     del fp_random
                     del sample_arrays
@@ -1127,26 +1127,29 @@ with tab2:
         with st.container():
                 tab1, tab2, tab3 = st.tabs(['Overall Exposures', 'CPT Exposures', 'FLEX 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.download_button(
-                        label="Export Exposures",
-                        data=convert_df_to_csv(player_freq),
-                        file_name='player_freq_export.csv',
-                        mime='text/csv',
-                    )
+                    if 'player_freq' in st.session_state:
+                        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),
+                            file_name='player_freq_export.csv',
+                            mime='text/csv',
+                        )
                 with tab2:
-                    st.dataframe(cpt_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(cpt_freq),
-                        file_name='cpt_freq_export.csv',
-                        mime='text/csv',
-                    )
+                    if 'player_freq' in st.session_state:
+                        st.dataframe(st.session_state.cpt_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.cpt_freq),
+                            file_name='cpt_freq_export.csv',
+                            mime='text/csv',
+                        )
                 with tab3:
-                    st.dataframe(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(flex_freq),
-                        file_name='flex_freq_export.csv',
-                        mime='text/csv',
-                    )
+                    if 'player_freq' in st.session_state:
+                        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),
+                            file_name='flex_freq_export.csv',
+                            mime='text/csv',
+                        )