Update position group selection in app.py by including 'UTIL' in the dict_columns for player data mapping, ensuring comprehensive data representation across all slate types.

app.py

@@ -190,7 +190,7 @@ def init_FD_lineups(type_var,slate_var):
 
                 raw_display = pd.DataFrame(list(cursor))
                 raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
-                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
                 # Map names
                 raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
             elif slate_var == 'Secondary':
@@ -204,7 +204,7 @@ def init_FD_lineups(type_var,slate_var):
 
                 raw_display = pd.DataFrame(list(cursor))
                 raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
-                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
                 # Map names
                 raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
             elif slate_var == 'Auxiliary':
@@ -218,7 +218,7 @@ def init_FD_lineups(type_var,slate_var):
             
                 raw_display = pd.DataFrame(list(cursor))
                 raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
-                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+                dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
                 # Map names
                 raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))