Update 'Top Score' handling in scoring percentages calculation in app.py to replace empty strings with NaN before casting to float, improving data integrity in player metrics analysis.

app.py

@@ -87,7 +87,7 @@ def init_baselines():
     scoring_percentages = scoring_percentages[['Names', 'Avg First Inning', 'First Inning Lead Percentage', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage', 'Avg Score', '8+ runs', 'Win Percentage', 'Slate', 'Top Score']]
     scoring_percentages['8+ runs'] = scoring_percentages['8+ runs'].replace('%', '', regex=True).astype(float)
     scoring_percentages['Win Percentage'] = scoring_percentages['Win Percentage'].replace('%', '', regex=True).astype(float)
-    scoring_percentages['Top Score'] = scoring_percentages['Top Score'].astype(float)
+    scoring_percentages['Top Score'] = scoring_percentages['Top Score'].replace('', np.nan).astype(float)
     dk_hitters_only = dk_roo[dk_roo['pos_group'] != 'Pitchers']
     dk_team_ownership = dk_hitters_only.groupby('Team')['Own%'].sum().reset_index()
     fd_hitters_only = fd_roo[fd_roo['pos_group'] != 'Pitchers']