Update app.py

app.py

@@ -66,14 +66,6 @@ def cleaning_features(data):
     
     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]])
-        race_encoded_cols = encoder.get_feature_names_out([N])
-        race_encoded_df = pd.DataFrame(race_encoded, columns=race_encoded_cols, index=data.index)
-        # Combine the encoded data with original dataframe
-        data = pd.concat([data.drop(N, axis=1), race_encoded_df], axis=1)
     # Binarize native country
     data['native-country'] = data['native-country'].apply(lambda x: x == 'United-States')
     data['native-country'] = data['native-country'].astype(int)