Refactor exposure_spread function to access salary and median values directly from the first row of comparable players, improving clarity and ensuring correct data retrieval for player comparisons.

global_func/exposure_spread.py

@@ -9,10 +9,10 @@ import random
 def exposure_spread(working_frame, exposure_player, exposure_target, exposure_stack_bool, projections_df):
     # Find comparable players in the projections
     comparable_players = projections_df[projections_df['player_names'] == exposure_player]
-    comp_salary_high = comparable_players['salary']
-    comp_salary_low = comparable_players['salary'] - 500
-    comp_projection_high = comparable_players['median']
-    comp_projection_low = comparable_players['median'] - (comparable_players['median'] * .9)
+    comp_salary_high = comparable_players['salary'][0]
+    comp_salary_low = comparable_players['salary'][0] - 500
+    comp_projection_high = comparable_players['median'][0]
+    comp_projection_low = comparable_players['median'][0] - (comparable_players['median'][0] * .9)
 
     comparable_players = projections_df[
         (projections_df['salary'] >= comp_salary_low) &