Update working_frame and export_base assignments in exposure_spread function to ensure consistent data handling and improve clarity in exposure evaluations.

app.py

@@ -1346,7 +1346,6 @@ with tab2:
                     if reg_submitted:
                         st.session_state['settings_base'] = False
                         parsed_frame = exposure_spread(st.session_state['working_frame'], exposure_player, exposure_target, exposure_stack_bool, remove_teams_exposure, st.session_state['projections_df'], sport_var, type_var, salary_max)
-                        st.session_state['working_frame'] = parsed_frame.reset_index(drop=True)
                         if type_var == 'Classic':
                             if sport_var == 'CS2' or sport_var == 'LOL':
                                 # Calculate salary (CPT uses cpt_salary_map, others use salary_map)
@@ -1398,6 +1397,7 @@ with tab2:
                                         sum(st.session_state['map_dict']['own_map'].get(player, 0) for player in row.iloc[1:]),
                                 axis=1
                             )
+                        st.session_state['working_frame'] = parsed_frame.reset_index(drop=True)
                         # st.session_state['working_frame']['Own'] = st.session_state['working_frame']['Own'].astype('float32')
                         st.session_state['working_frame']['median'] = st.session_state['working_frame']['median'].astype('float32')
                         st.session_state['working_frame']['salary'] = st.session_state['working_frame']['salary'].astype('uint16')
@@ -1408,7 +1408,7 @@ with tab2:
                     elif exp_submitted:
                         st.session_state['settings_base'] = False
                         parsed_frame = exposure_spread(st.session_state['export_base'], exposure_player, exposure_target, exposure_stack_bool, remove_teams_exposure, st.session_state['projections_df'], sport_var, type_var, salary_max)
-                        st.session_state['export_base'] = parsed_frame.reset_index(drop=True)
+                        
                         if type_var == 'Classic':
                             if sport_var == 'CS2' or sport_var == 'LOL':
                                 # Calculate salary (CPT uses cpt_salary_map, others use salary_map)
@@ -1460,6 +1460,7 @@ with tab2:
                                         sum(st.session_state['map_dict']['own_map'].get(player, 0) for player in row.iloc[1:]),
                                 axis=1
                             )
+                        st.session_state['export_base'] = parsed_frame.reset_index(drop=True)
                         # st.session_state['export_base']['Own'] = st.session_state['export_base']['Own'].astype('float32')
                         st.session_state['export_base']['median'] = st.session_state['export_base']['median'].astype('float32')
                         st.session_state['export_base']['salary'] = st.session_state['export_base']['salary'].astype('uint16')