Remove redundant player name mappings in VORP roster assignment to streamline data processing and enhance clarity in player rankings display.

src/streamlit_app.py

@@ -393,7 +393,7 @@ def assign_vorp_scoring(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict,
 
     return pos_des_dict, orig_rank_dict, half_ppr_match_dict, custom_match_dict
 
-def assign_vorp_roster(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, pos_vorp_limiters: dict, half_ppr_match_dict: dict, custom_match_dict: dict) -> pd.DataFrame:
+def assign_vorp_roster(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, pos_vorp_limiters: dict, half_ppr_match_dict: dict, custom_match_dict: dict, orig_rank_dict: dict) -> pd.DataFrame:
 
     vorp_frame = pd.DataFrame()
     for positions in ['QB', 'RB', 'WR', 'TE']:
@@ -402,6 +402,7 @@ def assign_vorp_roster(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, p
         pos_frame = pos_frame.sort_values(by='Rank', ascending=True).reset_index(drop=True)
         pos_frame['ranker_rank'] = pos_frame['Rank'].rank(method='first', ascending=True).astype(int)
         pos_frame['pos_rank_init'] = pos_frame['Pos'] + pos_frame['ranker_rank'].astype(str)
+        pos_frame['scoring_rank'] = pos_frame['Name'].map(orig_rank_dict)
         pos_frame['halfPpr_lu'] = pos_frame['pos_rank_init'].map(half_ppr_match_dict)
         pos_frame['custom_lu'] = pos_frame['pos_rank_init'].map(custom_match_dict)
         
@@ -447,10 +448,8 @@ def main():
     
     # Calculate VORP and rankings
     pos_des_dict, orig_rank_dict, half_ppr_match_dict, custom_match_dict = assign_vorp_scoring(position_df, halfPpr_rv, custom_scoring_rv, user_league_settings, user_pos_vorp_limiters)
-    final_df = assign_vorp_roster(position_df, halfPpr_rv, custom_roster_rv, user_pos_vorp_limiters, half_ppr_match_dict, custom_match_dict)
+    final_df = assign_vorp_roster(position_df, halfPpr_rv, custom_roster_rv, user_pos_vorp_limiters, half_ppr_match_dict, custom_match_dict, orig_rank_dict)
     final_df = final_df.drop(columns=['SR_ID'], axis=1)
-    final_df['Name_Lookup'] = final_df['Name'].map(orig_rank_dict)
-    final_df['Name'] = final_df['pos_des'].map(pos_des_dict)
     
     # Display results
     st.header("Player Rankings")