Update app.py

app.py

@@ -380,6 +380,8 @@ with tab3:
         display_baselines['cpt_lock'] = np.where(display_baselines['Player'].isin(lock_var1), 1, 0)
         display_baselines['lock'] = np.where(display_baselines['Player'].isin(lock_var2), 1, 0)
           
+        st.session_state.display_baselines = display_baselines.copy()
+        st.session_state.export_baselines = export_baselines.copy()
         
         index_check = pd.DataFrame()
         flex_proj = pd.DataFrame()
@@ -433,6 +435,8 @@ with tab3:
         combo_file = pd.concat([cpt_proj, flex_proj], ignore_index=True)
     
     with col2:
+        display_container = st.epmty()
+        display_dl_container = st.empty()
         optimize_container = st.empty()
         download_container = st.empty()
         freq_container = st.empty()
@@ -443,6 +447,8 @@ with tab3:
             max_own = 1000
             total_proj = 0
             total_own = 0
+            display_container = st.epmty()
+            display_dl_container = st.empty()
             optimize_container = st.empty()
             download_container = st.empty()
             freq_container = st.empty()
@@ -692,11 +698,26 @@ with tab3:
                             st.session_state.FD_final_outcomes_export = final_outcomes_export.copy()
           
                         st.session_state.player_freq = player_freq[['Player', 'Position', 'Team', 'Salary', 'Proj Own', 'Exposure']]
-                        
+        with display_container:
+                    display_container = st.empty()
+                    if 'display_baselines' in st.session_state:
+                        st.dataframe(st.session_state.display_baselines.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        
+        with display_dl_container:
+                    display_dl_container = st.empty()
+                    if 'export_baselines' in st.session_state:
+                        st.download_button(
+                            label="Export Projections",
+                            data=convert_df_to_csv(st.session_state.export_baselines),
+                            file_name='showdown_proj_export.csv',
+                            mime='text/csv',
+                        )        
+                
         with optimize_container:
                     optimize_container = st.empty()
                     if 'final_outcomes' in st.session_state:
                         st.dataframe(st.session_state.final_outcomes.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        
         with download_container:
             download_container = st.empty()
             if site_var1 == 'Draftkings':
@@ -715,6 +736,7 @@ with tab3:
                         file_name='FD_NFL_optimals_export.csv',
                         mime='text/csv',
                     )
+        
         with freq_container:
             freq_container = st.empty()
             if 'player_freq' in st.session_state: