Update app.py

app.py

@@ -78,17 +78,17 @@ def cleaning_features(data):
     data[numeric_cols] = scaler.transform(data[numeric_cols])
 
     for races in race_categories:
-        if data['race'] == race:
-            df[f'race_{races}'] = 1
+        if data['race'] == races:
+            data[f'race_{races}'] = 1
         else:
-            df[f'race_{races}'] = 0
+            data[f'race_{races}'] = 0
     # for N in columns_to_encode:
     #     race_encoded = encoder.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)
-    df = df.drop(columns=['race'])
+    data = data.drop(columns=['race'])
 
     data = pca(data)
     return data