Refactor selected rows handling in app.py: streamline the process of selecting and displaying top rows for each stack, enhancing user interaction and visibility of portfolio data.

app.py

@@ -920,32 +920,34 @@ with tab3:
                         else:
                             portfolio_copy = st.session_state['download_portfolio'].copy()
                         st.table(portfolio_copy)
-                        # Create a list to store selected rows
-                        selected_rows = []
-                        
-                        # For each stack, select the top N rows based on the count value
-                        for stack in unique_stacks:
-                            if stack in st.session_state.stack_multipliers:
-                                count = int(st.session_state.stack_multipliers[stack])
-                                # Get rows for this stack
-                                stack_rows = portfolio_copy[portfolio_copy['Stack'] == stack]
-                                # Sort by median and take top N rows
-                                top_rows = stack_rows.nlargest(count, sort_var)
-                                selected_rows.append(top_rows)
-                        
-                        # Combine all selected rows
-                        portfolio_copy = pd.concat(selected_rows)
-
-                        st.table(portfolio_copy)
-                        
-                        # Update export_file with filtered data
-                        export_file = portfolio_copy.copy()
-                        for col in export_file.columns:
-                            if col not in excluded_cols:
-                                export_file[col] = export_file[col].map(st.session_state['export_dict'])
                         
                         submitted = st.form_submit_button("Submit")
                         if submitted:
+                            # Create a list to store selected rows
+                            selected_rows = []
+                            
+                            # For each stack, select the top N rows based on the count value
+                            for stack in unique_stacks:
+                                if stack in st.session_state.stack_multipliers:
+                                    count = int(st.session_state.stack_multipliers[stack])
+                                    # Get rows for this stack
+                                    stack_rows = portfolio_copy[portfolio_copy['Stack'] == stack]
+                                    # Sort by median and take top N rows
+                                    top_rows = stack_rows.nlargest(count, sort_var)
+                                    selected_rows.append(top_rows)
+                            
+                            st.table(selected_rows)
+
+                            # Combine all selected rows
+                            portfolio_copy = pd.concat(selected_rows)
+
+                            st.table(portfolio_copy)
+                            
+                            # Update export_file with filtered data
+                            export_file = portfolio_copy.copy()
+                            for col in export_file.columns:
+                                if col not in excluded_cols:
+                                    export_file[col] = export_file[col].map(st.session_state['export_dict'])
                             st.write('Export portfolio updated!')
                             st.table(export_file)