Enhance data mapping for DraftKings and FanDuel in streamlit_app.py by implementing separate mappings for 'Regular' and 'Showdown' slate types. This improves data accuracy during export and ensures correct player IDs are used based on the selected site and slate type.

src/streamlit_app.py

@@ -1365,17 +1365,23 @@ if selected_tab == 'Optimals':
                 if site_var == 'Draftkings':
                     if type_var == 'Regular':
                         map_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
+                        for col_idx in map_columns:
+                            data_export[col_idx] = data_export[col_idx].map(dk_id_map)
                     elif type_var == 'Showdown':
                         map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
-                    for col_idx in map_columns:
-                        data_export[col_idx] = data_export[col_idx].map(dk_id_map)
+                        for col_idx in map_columns:
+                            data_export[col_idx] = data_export[col_idx].map(dk_sd_id_map)
+                    
                 elif site_var == 'Fanduel':
                     if type_var == 'Regular':
                         map_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
+                        for col_idx in map_columns:
+                            data_export[col_idx] = data_export[col_idx].map(fd_id_map)
                     elif type_var == 'Showdown':
                         map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
-                    for col_idx in map_columns:
-                        data_export[col_idx] = data_export[col_idx].map(fd_id_map)
+                        for col_idx in map_columns:
+                            data_export[col_idx] = data_export[col_idx].map(fd_sd_id_map)
+                    
                 data_export = data_export[data_export['salary'] >= salary_min_var]
                 data_export = data_export[data_export['salary'] <= salary_max_var]
                 data_export = data_export[data_export['Team_count'] >= min_stacks_var]
@@ -1481,17 +1487,21 @@ if selected_tab == 'Optimals':
     if site_var == 'Draftkings':
         if type_var == 'Regular':
             map_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
+            for col_idx in map_columns:
+                export_file[col_idx] = export_file[col_idx].map(dk_id_map)
         elif type_var == 'Showdown':
             map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
-        for col_idx in map_columns:
-            export_file[col_idx] = export_file[col_idx].map(dk_id_map)
+            for col_idx in map_columns:
+                export_file[col_idx] = export_file[col_idx].map(dk_sd_id_map)
     elif site_var == 'Fanduel':
         if type_var == 'Regular':
             map_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
+            for col_idx in map_columns:
+                export_file[col_idx] = export_file[col_idx].map(fd_id_map)
         elif type_var == 'Showdown':
             map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']
-        for col_idx in map_columns:
-            export_file[col_idx] = export_file[col_idx].map(fd_id_map)
+            for col_idx in map_columns:
+                export_file[col_idx] = export_file[col_idx].map(fd_sd_id_map)
             
     with st.container():
         if st.button("Reset Optimals", key='reset_optimals_button'):