Update app.py

app.py

@@ -31,14 +31,12 @@ def cleaning_features(data):
     numeric_cols = ['age', 'educational-num', 'hours-per-week']
     columns_to_encode = ['race','marital-status','relationship']
     
-    
-    # 1. Scale numerical features
-    data[numeric_cols] = scaler.fit_transform(data[numeric_cols])
-
-    # 2. Label encode gender and income
     data['gender'] = le.fit_transform(data['gender'])
     data['educational-num'] = le.fit_transform(data['educational-num'])
     
+    data[numeric_cols] = scaler.fit_transform(data[numeric_cols])
+    
+    
     # 3. One-hot encode race
     for N in columns_to_encode:
         race_encoded = encoder.fit_transform(data[[N]])