Update app.py

app.py

@@ -195,22 +195,21 @@ with tab2:
                         final_Proj = final_Proj[['Player', 'Minutes Proj', 'Position', 'Team', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '3x%', '4x%', '5x%', 'GPP%', 'Own', 'LevX', 'ValX']]
                         final_Proj = final_Proj.set_index('Player')
                         final_Proj = final_Proj.sort_values(by='Median', ascending=False)
+                        
+                        st.session_state.final_Proj = final_Proj
             
             with hold_container:
                 hold_container = st.empty()
                 
                 if pos_var1 == 'All':
-                    final_Proj = final_Proj
+                    st.session_state.final_Proj = st.session_state.final_Proj
                 elif pos_var1 != 'All':
-                    final_Proj = final_Proj[final_Proj['Position'].str.contains(pos_var1)]
-                st.dataframe(final_Proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+                    st.session_state.final_Proj = st.session_state.final_Proj[st.session_state.final_Proj['Position'].str.contains(pos_var1)]
+                st.dataframe(st.session_state.final_Proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
 
             st.download_button(
                         label="Export Tables",
-                        data=convert_df_to_csv(final_Proj),
+                        data=convert_df_to_csv(st.session_state.final_Proj),
                         file_name='Custom_NBA_export.csv',
                         mime='text/csv',
-            )
-
-with tab2:
-    st.info('Nothing here yet, but will be porting in a simple lineup optimizer soon')
+            )