Update 'Median' column handling in app.py: replace empty strings with zero before converting to float, ensuring robust data processing and preventing type-related issues during overall stats retrieval.

app.py

@@ -137,7 +137,7 @@ def load_overall_stats(league: str):
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
                                'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX', 'site', 'version', 'slate', 'timestamp', 'player_id']]
-    raw_display['Median'] = raw_display['Median'].astype(float)
+    raw_display['Median'] = raw_display['Median'].replace('', 0).astype(float)
     raw_display = raw_display.rename(columns={"player_id": "player_ID"})
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
@@ -163,7 +163,7 @@ def load_overall_stats(league: str):
         raw_display = raw_display[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
                                 'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX', 'site', 'version', 'slate', 'timestamp', 'player_id']]
         raw_display = raw_display.rename(columns={"player_id": "player_ID"})
-    raw_display['Median'] = raw_display['Median'].astype(float)
+    raw_display['Median'] = raw_display['Median'].replace('', 0).astype(float)
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     roo_raw = raw_display.sort_values(by='Median', ascending=False)