Reintroduce salary cap filtering for working frame in app.py to ensure only eligible players are loaded. This update enhances data integrity and aligns with previous optimizations for memory efficiency.

app.py

@@ -1327,7 +1327,6 @@ 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
@@ -1339,6 +1338,7 @@ if selected_tab == 'Manage Portfolio':
                 sport_var, 
                 st.session_state['projections_df'] if 'stack_dict' in st.session_state else None
             )
+            st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['salary'] <= salary_max]
             
             # Map existing stack/size data if available
             if 'stack_dict' in st.session_state: