Refactor combined dataframe handling in app.py for improved clarity and performance

- Simplified the logic for managing the combined dataframe by removing unnecessary checks for 'portfolio_df', ensuring consistent handling of contest data.
- Streamlined vectorized string operations to directly apply to the 'Contest' dataframe, enhancing data integrity.
- Updated the working dataframe assignment to always reference 'Contest', improving code readability and maintainability.

app.py

@@ -212,10 +212,11 @@ with tab1:
             if 'portfolio_df' in st.session_state:
                 st.write('Portfolio data:')
                 st.dataframe(st.session_state['portfolio_df'].head(25))
-                st.session_state['combined_df'] = pd.concat([st.session_state['Contest'], st.session_state['portfolio_df']], ignore_index=True)
-                st.session_state['combined_df'] = st.session_state['combined_df'].reset_index(drop=True)
-                st.dataframe(st.session_state['combined_df'][st.session_state['combined_df']['BaseName'] == 'Backtesting_upload'].head(25))
+                combined_df = pd.concat([st.session_state['Contest'], st.session_state['portfolio_df']], ignore_index=True)
+                combined_df = combined_df.reset_index(drop=True)
+                st.dataframe(combined_df[combined_df['BaseName'] == 'Backtesting_upload'].head(25))
                 st.session_state['entry_list'].append('Backtesting_upload')
+                st.session_state['Contest'] = combined_df
             else:
                 pass
         
@@ -230,20 +231,13 @@ with tab2:
     excluded_cols = ['BaseName', 'EntryCount']
     exclude_stacks = ['BaseName', 'EntryCount', 'SP', 'SP1', 'SP2', 'P1', 'P2']
     if 'Contest' in st.session_state and 'display_contest_info' not in st.session_state:
-        if 'portfolio_df' in st.session_state:
-            st.session_state['player_columns'] = [col for col in st.session_state['combined_df'].columns if col not in excluded_cols]
-            st.session_state['stack_columns'] = [col for col in st.session_state['combined_df'].columns if col not in exclude_stacks]
-        else:
-            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]
+        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'])
         
         # Vectorized string operations
         for col in st.session_state['player_columns']:
-            if 'portfolio_df' in st.session_state:
-                st.session_state['combined_df'][col] = st.session_state['combined_df'][col].astype(str).str.strip()
-            else:
-                st.session_state['Contest'][col] = st.session_state['Contest'][col].astype(str).str.strip()
+            st.session_state['Contest'][col] = st.session_state['Contest'][col].astype(str).str.strip()
     
         # Create mapping dictionaries
         st.session_state['map_dict'] = {
@@ -254,13 +248,8 @@ with tab2:
             'own_percent_rank': dict(zip(st.session_state['ownership_df']['Player'], st.session_state['ownership_df']['Own'].rank(pct=True)))
         }
         
-        # Create a copy of the dataframe for calculations
-        if 'portfolio_df' in st.session_state:
-            working_df = st.session_state['combined_df'].copy()
-        else:
-            working_df = st.session_state['Contest'].copy()
-        
-        st.write(working_df[working_df['BaseName'] == 'Backtesting_upload'])
+
+        working_df = st.session_state['Contest'].copy()
         
         # Pre-compute lookup arrays for vectorized operations
         team_map = st.session_state['map_dict']['team_map']