Update trimming dictionary initialization in app.py: ensure consistent handling of maximum values for ownership types during portfolio updates, improving state management and preventing data conflicts.

app.py

@@ -944,6 +944,14 @@ with tab2:
                     if submitted:
                         st.write('initiated')
                         st.session_state['portfolio'] = predict_dupes(st.session_state['portfolio'], map_dict, site_var, type_var, Contest_Size, strength_var, sport_var)
+                        if 'trimming_dict_maxes' not in st.session_state:
+                            st.session_state['trimming_dict_maxes'] = {
+                                'Own': st.session_state['portfolio']['Own'].max(),
+                                'Geomean': st.session_state['portfolio']['Geomean'].max(),
+                                'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
+                                'median': st.session_state['portfolio']['median'].max(),
+                                'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
+                            }
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Dupes'] <= max_dupes]
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] >= min_salary]
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= max_salary]
@@ -979,16 +987,14 @@ with tab2:
         with col2:
             st.write('initiated')
             st.session_state['portfolio'] = predict_dupes(st.session_state['portfolio'], map_dict, site_var, type_var, Contest_Size, strength_var, sport_var)
-            if 'trimming_dict_maxes' in st.session_state:
-                del st.session_state['trimming_dict_maxes']
-            
-            st.session_state['trimming_dict_maxes'] = {
-                'Own': st.session_state['portfolio']['Own'].max(),
-                'Geomean': st.session_state['portfolio']['Geomean'].max(),
-                'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
-                'median': st.session_state['portfolio']['median'].max(),
-                'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
-            }
+            if 'trimming_dict_maxes' not in st.session_state:
+                st.session_state['trimming_dict_maxes'] = {
+                    'Own': st.session_state['portfolio']['Own'].max(),
+                    'Geomean': st.session_state['portfolio']['Geomean'].max(),
+                    'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
+                    'median': st.session_state['portfolio']['median'].max(),
+                    'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
+                }
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Dupes'] <= max_dupes]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] >= min_salary]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= max_salary]