Update stack column handling in app.py

- Introduced a new list of excluded stack columns to enhance data processing for contest entries.
- Updated the logic for determining the 'stack' and 'stack_size' in the working DataFrame to utilize the new stack columns, improving accuracy in data representation.

app.py

@@ -197,8 +197,10 @@ with tab1:
 
 with tab2:
     excluded_cols = ['BaseName', 'EntryCount']
+    exclude_stacks = ['BaseName', 'EntryCount', 'SP', 'SP1', 'SP2']
     if 'Contest' in st.session_state and 'display_contest_info' not in st.session_state:
         st.session_state['player_columns'] = [col for col in st.session_state['Contest'].columns if col not in excluded_cols]
+        st.session_state['stack_columns'] = [col for col in st.session_state['Contest'].columns if col not in exclude_stacks]
         print(st.session_state['player_columns'])
         for col in st.session_state['player_columns']:
             st.session_state['Contest'][col] = st.session_state['Contest'][col].astype(str).str.strip()
@@ -217,16 +219,16 @@ with tab2:
         if type_var == 'Classic':
             working_df['stack'] = working_df.apply(
                 lambda row: Counter(
-                    st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['player_columns']]
+                    st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['stack_columns']]
                     if st.session_state['map_dict']['team_map'].get(player, '') != ''
-                ).most_common(1)[0][0] if any(st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['player_columns']]) else '',
+                ).most_common(1)[0][0] if any(st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['stack_columns']]) else '',
                 axis=1
             )
             working_df['stack_size'] = working_df.apply(
                 lambda row: Counter(
-                    st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['player_columns']]
+                    st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['stack_columns']]
                     if st.session_state['map_dict']['team_map'].get(player, '') != ''
-                ).most_common(1)[0][1] if any(st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['player_columns']]) else '',
+                ).most_common(1)[0][1] if any(st.session_state['map_dict']['team_map'].get(player, '') for player in row[st.session_state['stack_columns']]) else '',
                 axis=1
             )
             working_df['salary'] = working_df.apply(lambda row: sum(st.session_state['salary_dict'].get(player, 0) for player in row[st.session_state['player_columns']]), axis=1)