Update 'Order' column type to integer and add 'Runs/$' calculation in scoring percentages DataFrame in app.py for improved data accuracy and analysis capabilities.

app.py

@@ -82,7 +82,7 @@ def init_baselines():
     hold_frame['Hand'] = np.where(hold_frame['pos_group'] == 'Hitters', hold_frame['Player'].map(RHP_Info.set_index('Player')['bats']), '')
 
     roo_data.insert(3, 'Hand', hold_frame['Hand'])
-    roo_data.insert(4, 'Order', hold_frame['Order'])
+    roo_data.insert(4, 'Order', hold_frame['Order'].astype(int))
     
     dk_roo = roo_data[roo_data['Site'] == 'Draftkings']
     dk_id_map = dict(zip(dk_roo['Player'], dk_roo['player_ID']))
@@ -101,7 +101,8 @@ def init_baselines():
     cursor = collection.find()
     team_frame = pd.DataFrame(cursor)
     scoring_percentages = team_frame.drop(columns=['_id'])
-    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', '8+ runs', 'Win Percentage',
+    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',
     '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)