Update exposure_spread function to utilize numpy for player location identification, enhancing accuracy in lineup adjustments by ensuring the correct player is replaced with a comparable player from the list.

global_func/exposure_spread.py

@@ -1,4 +1,5 @@
 import random
+import numpy as np
 
 #### Goal is to choose a player and adjust the amount of lineups that have them
 #### First thing you need to do is find comparable players in the projections, so any player in the projections that is within $500 of the player and within 10% of the projection
@@ -38,7 +39,8 @@ def exposure_spread(working_frame, exposure_player, exposure_target, exposure_st
 
     # for each row, replace with random choice from comparable player list
     for row in player_rows.index:
-        working_frame.at[row, 'player_names'] = random.choice(comparable_player_list)
+        player_location = np.where(working_frame.iloc[row] == exposure_player)
+        working_frame.at[player_location[0], player_location[1]] = random.choice(comparable_player_list)
 
     return working_frame