Update scoring percentages calculation in app.py to include separate metrics for DraftKings and FanDuel. This change enhances the data structure by introducing 'DK_Runs/$' and 'FD_Runs/$', while also refining the handling of average salary columns for each platform, improving overall data accuracy for player selection.

app.py

@@ -158,8 +158,9 @@ def init_baselines():
     cursor = collection.find()
     team_frame = pd.DataFrame(cursor)
     scoring_percentages = team_frame.drop(columns=['_id'])
-    scoring_percentages['Runs/$'] = scoring_percentages['Avg Score'] / (scoring_percentages['Avg_Salary'] / 1000)
-    scoring_percentages = scoring_percentages[['Names', 'Avg_Salary', 'Stack_Prio', 'Opp_SP', 'Avg First Inning', 'First Inning Lead Percentage', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage', 'Avg Score', 'Runs/$', '8+ runs', 'Win Percentage',
+    scoring_percentages['DK_Runs/$'] = scoring_percentages['Avg Score'] / (scoring_percentages['Avg_Salary_DK'] / 1000)
+    scoring_percentages['FD_Runs/$'] = scoring_percentages['Avg Score'] / (scoring_percentages['Avg_Salary_FD'] / 1000)
+    scoring_percentages = scoring_percentages[['Names', 'Avg_Salary_DK', 'Avg_Salary_FD', 'Stack_Prio', 'Opp_SP', 'Avg First Inning', 'First Inning Lead Percentage', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage', 'Avg Score', 'DK_Runs/$', 'FD_Runs/$', '8+ runs', 'Win Percentage',
     'DK Main Slate', 'DK Secondary Slate', 'DK Turbo Slate', 'FD Main Slate', 'FD Secondary Slate', 'FD Turbo Slate', 'DK Main Top Score', 'FD Main Top Score', 'DK Secondary Top Score', 'FD Secondary Top Score',
     'DK Turbo Top Score', 'FD Turbo Top Score']]
     scoring_percentages['8+ runs'] = scoring_percentages['8+ runs'].replace('%', '', regex=True).astype(float)
@@ -426,11 +427,11 @@ with tab1:
             scoring_percentages = scoring_percentages.drop(['DK Main Slate', 'DK Secondary Slate', 'DK Turbo Slate', 'FD Main Slate', 'FD Secondary Slate', 'FD Turbo Slate', 'FD Main Top Score', 'DK Main Top Score', 'FD Secondary Top Score', 'DK Secondary Top Score', 'DK Turbo Top Score'], axis=1)
     scoring_percentages = scoring_percentages.sort_values(by='8+ runs', ascending=False)
     if site_var == 'Draftkings':
-        scoring_percentages = scoring_percentages.rename(columns={'DK LevX': 'LevX', 'DK Own%': 'Own%', 'Avg Score': 'Runs', 'Win Percentage': 'Win%', '8+ runs': '8+ Runs'})
-        scoring_percentages = scoring_percentages.drop(['FD Own%'], axis=1)
+        scoring_percentages = scoring_percentages.rename(columns={'DK LevX': 'LevX', 'DK Own%': 'Own%', 'Avg Score': 'Runs', 'Win Percentage': 'Win%', '8+ runs': '8+ Runs', 'Avg_Salary_DK': 'Avg_Salary'})
+        scoring_percentages = scoring_percentages.drop(['FD Own%', 'FD_Runs/$', 'Avg_Salary_FD'], axis=1)
     elif site_var == 'Fanduel':
-        scoring_percentages = scoring_percentages.rename(columns={'FD LevX': 'LevX', 'FD Own%': 'Own%', 'Avg Score': 'Runs', 'Win Percentage': 'Win%', '8+ runs': '8+ Runs'})
-        scoring_percentages = scoring_percentages.drop(['DK Own%'], axis=1)
+        scoring_percentages = scoring_percentages.rename(columns={'FD LevX': 'LevX', 'FD Own%': 'Own%', 'Avg Score': 'Runs', 'Win Percentage': 'Win%', '8+ runs': '8+ Runs', 'Avg_Salary_FD': 'Avg_Salary'})
+        scoring_percentages = scoring_percentages.drop(['DK Own%', 'DK_Runs/$', 'Avg_Salary_DK'], axis=1)
     
     if view_var == "Simple":
         scoring_percentages = scoring_percentages[['Names', 'Runs', '8+ Runs', 'Win%', 'LevX', 'Own%']]