ping

app.py

@@ -1296,60 +1296,60 @@ with tab2:
                         st.session_state['export_base'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
                         st.session_state['export_merge'] = st.session_state['export_base'].copy()
             
-            with st.expander('Conditional Manager'):
-                # a set of functions for removing lineups that contain a conditional between players and stacks
-                with st.form(key='conditional_manager_form'):
-                    player_names = set()
-                    for col in st.session_state['working_frame'].columns:
-                        if col not in excluded_cols:
-                            player_names.update(st.session_state['working_frame'][col].unique())
-                    conditional_remove_players = st.multiselect("Remove lineups containing player(s):", options=sorted(list(player_names)), default=[])
-                    conditional_include_players = st.multiselect("If they also contain player(s):", options=sorted(list(player_names)), default=[])
+            # with st.expander('Conditional Manager'):
+            #     # a set of functions for removing lineups that contain a conditional between players and stacks
+            #     with st.form(key='conditional_manager_form'):
+            #         player_names = set()
+            #         for col in st.session_state['working_frame'].columns:
+            #             if col not in excluded_cols:
+            #                 player_names.update(st.session_state['working_frame'][col].unique())
+            #         conditional_remove_players = st.multiselect("Remove lineups containing player(s):", options=sorted(list(player_names)), default=[])
+            #         conditional_include_players = st.multiselect("If they also contain player(s):", options=sorted(list(player_names)), default=[])
                     
-                    submitted_col, export_col = st.columns(2)
-                    st.info("Portfolio Button applies to your overall Portfolio, Export button applies to your Custom Export")
-                    with submitted_col:
-                        reg_submitted = st.form_submit_button("Portfolio")
-                    with export_col:
-                        exp_submitted = st.form_submit_button("Export")
-                    if reg_submitted:
-                        st.session_state['settings_base'] = False
-                        parsed_frame = st.session_state['working_frame'].copy()
-
-                        player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
-
-                        # Test with a simpler approach
-                        include_mask = parsed_frame[player_columns].apply(
-                            lambda row: all(player in row.values for player in conditional_include_players), axis=1
-                        )
+            #         submitted_col, export_col = st.columns(2)
+            #         st.info("Portfolio Button applies to your overall Portfolio, Export button applies to your Custom Export")
+            #         with submitted_col:
+            #             reg_submitted = st.form_submit_button("Portfolio")
+            #         with export_col:
+            #             exp_submitted = st.form_submit_button("Export")
+            #         if reg_submitted:
+            #             st.session_state['settings_base'] = False
+            #             parsed_frame = st.session_state['working_frame'].copy()
+
+            #             player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
+
+            #             # Test with a simpler approach
+            #             include_mask = parsed_frame[player_columns].apply(
+            #                 lambda row: all(player in row.values for player in conditional_include_players), axis=1
+            #             )
                             
-                        remove_mask = parsed_frame[player_columns].apply(
-                            lambda row: not any(player in row.values for player in conditional_remove_players), axis=1
-                        )
+            #             remove_mask = parsed_frame[player_columns].apply(
+            #                 lambda row: not any(player in row.values for player in conditional_remove_players), axis=1
+            #             )
                         
-                        parsed_frame = parsed_frame[include_mask & remove_mask]
+            #             parsed_frame = parsed_frame[include_mask & remove_mask]
 
-                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
-                        st.session_state['export_merge'] = st.session_state['working_frame'].copy()
-                    elif exp_submitted:
-                        st.session_state['settings_base'] = False
-                        parsed_frame = st.session_state['export_base'].copy()
+            #             st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
+            #             st.session_state['export_merge'] = st.session_state['working_frame'].copy()
+            #         elif exp_submitted:
+            #             st.session_state['settings_base'] = False
+            #             parsed_frame = st.session_state['export_base'].copy()
                         
-                        player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
+            #             player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
                         
-                        # Test with a simpler approach
-                        include_mask = parsed_frame[player_columns].apply(
-                            lambda row: all(player in row.values for player in conditional_include_players), axis=1
-                        )
+            #             # Test with a simpler approach
+            #             include_mask = parsed_frame[player_columns].apply(
+            #                 lambda row: all(player in row.values for player in conditional_include_players), axis=1
+            #             )
                             
-                        remove_mask = parsed_frame[player_columns].apply(
-                            lambda row: not any(player in row.values for player in conditional_remove_players), axis=1
-                        )
+            #             remove_mask = parsed_frame[player_columns].apply(
+            #                 lambda row: not any(player in row.values for player in conditional_remove_players), axis=1
+            #             )
                         
-                        parsed_frame = parsed_frame[include_mask & remove_mask]
+            #             parsed_frame = parsed_frame[include_mask & remove_mask]
                         
-                        st.session_state['export_base'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
-                        st.session_state['export_merge'] = st.session_state['export_base'].copy()
+            #             st.session_state['export_base'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
+            #             st.session_state['export_merge'] = st.session_state['export_base'].copy()
 
             with st.expander('Trimming Options'):
                 with st.form(key='trim_form'):

global_func/predict_dupes.py

@@ -594,7 +594,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
         portfolio['own_sum'] / portfolio['own_average'],
         (portfolio['own_sum'] - max_ownership) / portfolio['own_average']
     )
-    percentile_cut_scalar = portfolio['median'].max()  # Get scalar value
+    percentile_cut_scalar = portfolio['median'].max()
     if type_var == 'Classic':
         if sport_var == 'CS2':
             own_ratio_nerf = 2