Update app.py

app.py

@@ -112,17 +112,24 @@ overall_dem = init_baselines()
 if st.button("Reset Data", key='reset1'):
           st.cache_data.clear()
           overall_dem = init_baselines()
-# split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
-# if split_var1 == 'Specific Teams':
-#     team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = public_minutes['TC'].unique(), key='team_var1')
-# elif split_var1 == 'All':
-#     team_var1 = public_minutes.TC.values.tolist()
-# public_minutes = public_minutes[public_minutes['TC'].isin(team_var1)]
-# player_min_disp = public_minutes.set_index('Player')
-# player_min_disp = player_min_disp.sort_values(by=['TC', 'MP (Today)'], ascending=[True, False])
-st.dataframe(overall_dem.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
+if split_var1 == 'Specific Teams':
+    team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['Acro'].unique(), key='team_var1')
+elif split_var1 == 'All':
+    team_var1 = overall_dem.Acro.values.tolist()
+split_var2 = st.radio("Would you like to view all positions or specific ones?", ('All', 'Specific Positions'), key='split_var2')
+if split_var2 == 'Specific Positions':
+    pos_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['position'].unique(), key='pos_var1')
+elif split_var2 == 'All':
+    pos_var1 = overall_dem.position.values.tolist()
+dem_display = overall_dem[overall_dem['Acro'].isin(team_var1)]
+dem_display = dem_display[dem_display['position'].isin(pos_var1)]
+dem_display = dem_display.sort_values(by='FPPM Boost', ascending=False)
+dem_display.rename(columns={"Acro": "Team (Giving Boost)"}, inplace = True)
+dem_display = dem_display.drop('index')
+st.dataframe(dem_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
 st.download_button(
-    label="Export Minutes Baselines",
+    label="Export DEM Numbers",
     data=convert_df_to_csv(overall_dem),
     file_name='DEM_export.csv',
     mime='text/csv',