Update app.py

app.py

@@ -109,28 +109,30 @@ def convert_df_to_csv(df):
 
 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 = 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 DEM Numbers",
-    data=convert_df_to_csv(overall_dem),
-    file_name='DEM_export.csv',
-    mime='text/csv',
-)
+col1, col2 = st.columns()
+with col1:
+    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 = 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()
+with col2:
+    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)
+    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 DEM Numbers",
+        data=convert_df_to_csv(overall_dem),
+        file_name='DEM_export.csv',
+        mime='text/csv',
+    )