Update app.py

app.py

@@ -590,11 +590,19 @@ def server(input, output, session):
 
 
 
-        df_test_merge = df_test_merge.select([
-            'Player ID','Batter','Bats', 'GP', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'C', '1B', '2B', '3B', 'SS', 'LF', 'CF', 'RF', 'DH', 'LHP', 'RHP'
-        ])
-
-        # First convert your data to hierarchical columns
+        # List of desired columns
+        desired_columns = [
+            'Player ID', 'Batter', 'Bats', 'GP', '1', '2', '3', '4', '5', '6', '7', '8', '9',
+            'C', '1B', '2B', '3B', 'SS', 'LF', 'CF', 'RF', 'DH', 'LHP', 'RHP'
+        ]
+        
+        # Check for existing columns and select safely
+        existing_columns = [col for col in desired_columns if col in df_test_merge.columns]
+        
+        # Select existing columns
+        df_test_merge = df_test_merge.select(existing_columns)
+        
+        # Continue with the rest of the code
         cols = {
             ('Player Info', 'Player ID'): 'Player ID',
             ('Player Info', 'Batter'): 'Batter',
@@ -621,18 +629,15 @@ def server(input, output, session):
             ('Pitcher', 'LHP'): 'LHP',
             ('Pitcher', 'RHP'): 'RHP'
         }
-        # Assuming your polars DataFrame is called df
+        
         # Convert to pandas
         df_pandas = df_test_merge.to_pandas()
-
-
+        
+        # Replace 0 with ''
         df_pandas = df_pandas.replace({0: ''})
-
+        
         # Rename columns with multi-index
-        df_pandas.columns = pd.MultiIndex.from_tuples(
-            [(k[0], k[1]) for k in cols.keys()]
-        )
-
+        df_pandas.columns = pd.MultiIndex.from_tuples([(k[0], k[1]) for k in cols.keys()])
 
         df_pivot_style = df_pandas.style
         thick_border_cols = [3, 4, 13,22]  # 0-based index