Refactor QB rank adjustment logic in VORP calculation to use vectorized operations, improving performance and maintaining accuracy for Standard and PPR league types.

src/streamlit_app.py

@@ -395,11 +395,9 @@ def assign_vorp(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, league_s
     for positions in ['QB', 'RB', 'WR', 'TE']:
         vorp_frame.loc[vorp_frame['Pos'] == positions, 'Rank_Adjust'] = (vorp_frame['Rank'] - (vorp_frame['vorp_diff'] * pos_vorp_limiters[positions])).astype(float)
     if league_settings['TYPE'] == 'Standard':
-        if vorp_frame['Pos'] == 'QB':
-            vorp_frame['Rank_Adjust'] = max(vorp_frame['Rank_Adjust'], 10)
+        vorp_frame.loc[vorp_frame['Pos'] == 'QB', 'Rank_Adjust'] = vorp_frame.loc[vorp_frame['Pos'] == 'QB', 'Rank_Adjust'].apply(lambda x: max(x, 10))
     elif league_settings['TYPE'] == 'PPR':
-        if vorp_frame['Pos'] == 'QB':
-            vorp_frame['Rank_Adjust'] = max(vorp_frame['Rank_Adjust'], -10)
+        vorp_frame.loc[vorp_frame['Pos'] == 'QB', 'Rank_Adjust'] = vorp_frame.loc[vorp_frame['Pos'] == 'QB', 'Rank_Adjust'].apply(lambda x: max(x, -10))
     pos_lock_dict = dict(zip(vorp_frame['pos_lock'], vorp_frame['Name']))
     name_lock_dict = dict(zip(vorp_frame['Name'], vorp_frame['pos_lock']))
     vorp_frame['custom_rank'] = vorp_frame['Rank_Adjust'].rank(method='first', ascending=True).astype(int)