Update app.py

app.py

@@ -86,7 +86,7 @@ with col1:
               del st.session_state[key]
           DK_seed, FD_seed, dk_raw, fd_raw = init_baselines()
           
-    slate_var1 = st.radio("Which data are you loading?", ('Main Slate'))
+    slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Other Main Slate'))
     site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
     if site_var1 == 'Draftkings':
         raw_baselines = dk_raw
@@ -114,19 +114,36 @@ with col2:
     if site_var1 == 'Draftkings':
         st.session_state.Sim_Winner_Frame = DK_seed.head(Contest_Size)
         st.session_state.Sim_Winner_Display = DK_seed.head(Contest_Size)
+        st.session_state.Sim_Winner_Export = DK_seed
         st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:9].values, return_counts=True)),
                                     columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
         st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
         st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(Contest_Size)
-
+        
+        if 'Sim_Winner_Export' in st.session_state:
+                st.download_button(
+                    label="Export 500k optimals",
+                    data=st.session_state.Sim_Winner_Export.to_csv().encode('utf-8'),
+                    file_name='MLB_consim_export.csv',
+                    mime='text/csv',
+                )
         st.dataframe(st.session_state.Sim_Winner_Display.style.format(precision=2), height=500, use_container_width=True)
         st.dataframe(st.session_state.player_freq.style.format(percentages_format, precision=2), height=500, use_container_width=True)
     elif site_var1 == 'Fanduel':
         st.session_state.Sim_Winner_Frame = FD_seed.head(Contest_Size)
         st.session_state.Sim_Winner_Display = FD_seed.head(Contest_Size)
+        st.session_state.Sim_Winner_Export = FD_seed
         st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:8].values, return_counts=True)),
                                     columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
         st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
         st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(Contest_Size)
+        
+        if 'Sim_Winner_Export' in st.session_state:
+                st.download_button(
+                    label="Export 500k optimals",
+                    data=st.session_state.Sim_Winner_Export.to_csv().encode('utf-8'),
+                    file_name='MLB_consim_export.csv',
+                    mime='text/csv',
+                )
         st.dataframe(st.session_state.Sim_Winner_Display.style.format(precision=2), height=500, use_container_width=True)
         st.dataframe(st.session_state.player_freq.style.format(percentages_format, precision=2), height=500, use_container_width=True)