Remove match_back_dict from VORP scoring and roster assignment functions in Streamlit app to streamline player name mapping, enhancing clarity and simplifying function signatures.

src/streamlit_app.py

@@ -387,14 +387,13 @@ def assign_vorp_scoring(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict,
     orig_rank_dict = dict(zip(vorp_frame['Name'], vorp_frame['pos_designation']))
     half_ppr_match_dict = dict(zip(vorp_frame['pos_designation'], vorp_frame['halfPpr']))
     custom_match_dict = dict(zip(vorp_frame['pos_designation'], vorp_frame[rv_type]))
-    match_back_dict = dict(zip(vorp_frame[rv_type], vorp_frame['Name']))
 
     for pos in ['QB', 'RB', 'WR', 'TE']:
         print(vorp_frame[vorp_frame['Pos'] == pos].head(20))
 
-    return pos_des_dict, orig_rank_dict, half_ppr_match_dict, custom_match_dict, match_back_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, match_back_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) -> pd.DataFrame:
 
     vorp_frame = pd.DataFrame()
     for positions in ['QB', 'RB', 'WR', 'TE']:
@@ -421,7 +420,6 @@ def assign_vorp_roster(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, p
     vorp_frame['custom_rank'] = vorp_frame['Rank_Adjust'].rank(method='first', ascending=True).astype(int)
     vorp_frame['pos_rank'] = vorp_frame.groupby('Pos')['custom_rank'].rank(method='first', ascending=True).astype(int)
     vorp_frame['pos_des'] = vorp_frame['Pos'] + vorp_frame['pos_rank'].astype(str)
-    vorp_frame['Name'] = vorp_frame['custom_lu'].map(match_back_dict)
 
     return vorp_frame.sort_values(by='custom_rank', ascending=True)
 
@@ -452,6 +450,7 @@ def main():
     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 = 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")