Update app.py

app.py

@@ -37,8 +37,7 @@ gcservice_account = init_conn()
 NHL_data = 'https://docs.google.com/spreadsheets/d/1NmKa-b-2D3w7rRxwMPSchh31GKfJ1XcDI2GU8rXWnHI/edit#gid=811139250'
 
 percentages_format = {'Shots': '{:.2%}', 'HDCF': '{:.2%}', 'Goals': '{:.2%}', 'Assists': '{:.2%}', 'Blocks': '{:.2%}',
-                      'L14_Shots': '{:.2%}', 'L14_HDCF': '{:.2%}', 'L14_Goals': '{:.2%}', 'L14_Assists': '{:.2%}',
-                      'L14_Blocks': '{:.2%}', 'Max Goal%': '{:.2%}'}
+                      'L14_Shots': '{:.2%}', 'L14_HDCF': '{:.2%}', 'L14_Goals': '{:.2%}', 'L14_Assists': '{:.2%}', 'L14_Blocks': '{:.2%}'}
 
 @st.cache_resource(ttl = 599)
 def init_baselines():
@@ -77,17 +76,10 @@ def init_baselines():
     # raw_display = raw_display[raw_display['Line'] != ""]
     overall_ms = raw_display[['Line', 'SK1', 'SK2', 'SK3', 'Cost', 'Team Total', 'Shots', 'HDCF', 'Goals', 'Assists', 'Blocks',
                               'L14_Shots', 'L14_HDCF', 'L14_Goals', 'L14_Assists', 'L14_Blocks']]
-    for team in team_list:
-        table_parsed = overall_ms[overall_ms['Line'].str.contains('|'.join(team))]
-        table_parsed['Max Goal%'] = table_parsed['Goals'].max()
-        
-        parse_hold = pd.concat([parse_hold, table_parsed])
-    
-    overall_ms = parse_hold
     data_cols = overall_ms.columns.drop(['Line', 'SK1', 'SK2', 'SK3'])
     overall_ms[data_cols] = overall_ms[data_cols].apply(pd.to_numeric, errors='coerce')
     overall_ms = overall_ms.sort_values(by='Shots', ascending=False)
-    
+        
     return matchups, overall_ms, team_frame, team_list, team_dict
 
 def convert_df_to_csv(df):
@@ -121,7 +113,7 @@ with col2:
     elif split_var1 == 'Line Marketshares':
         display_table = overall_ms
         display_parsed = display_table[display_table['Line'].str.contains('|'.join(team_split))]
-        st.dataframe(display_parsed, use_container_width = True)
+        st.dataframe(display_parsed.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
         st.download_button(
             label="Export Marketshares",
             data=convert_df_to_csv(display_table),