fixed minutes proj

app.py

@@ -103,7 +103,7 @@ def load_overall_stats():
     cursor = collection.find()
 
     raw_display = pd.DataFrame(list(cursor))
-    raw_display = raw_display[['Player', 'Minutes', 'Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Cei', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
+    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']]
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
@@ -115,7 +115,7 @@ def load_overall_stats():
     cursor = collection.find()
 
     raw_display = pd.DataFrame(list(cursor))
-    raw_display = raw_display[['Player', 'Minutes', 'Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Cei', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
+    raw_display = raw_display[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Cei', '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', 'Date']]
     roo_backlog = raw_display.sort_values(by='Date', ascending=False)
     roo_backlog = roo_backlog[roo_backlog['slate'] == 'Main Slate']