Update portfolio management in app.py to reintroduce salary cap filtering for working frame. This change ensures that only eligible players are loaded into the working frame, enhancing data integrity and memory efficiency.

app.py

@@ -777,7 +777,7 @@ if selected_tab == 'Data Load':
                 st.session_state['map_dict'] = create_memory_efficient_mappings(st.session_state['projections_df'], site_var, type_var, sport_var)
             
             # Store portfolio in compressed format and clean up
-            st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= salary_max]
+            # st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= salary_max]
             buffer = io.BytesIO()
             st.session_state['portfolio'].to_parquet(buffer, compression='snappy')
             st.session_state['origin_portfolio'] = buffer.getvalue()
@@ -1327,6 +1327,7 @@ if selected_tab == 'Manage Portfolio':
         if 'working_frame' not in st.session_state:
             st.session_state['settings_base'] = True
             st.session_state['working_frame'] = pd.read_parquet(io.BytesIO(st.session_state['origin_portfolio']))
+            st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['salary'] <= salary_max]
             st.session_state['player_columns'] = [col for col in st.session_state['working_frame'].columns if col not in excluded_cols]
             
             # Use vectorized calculation function