code: def test_mode_imputation_with_multiple_variables(df_na):
      # set up imputer
      imputer = CategoricalImputer(
          imputation_method="frequent", variables=["Studies", "City"]
      )
      X_transformed = imputer.fit_transform(df_na)
  
      # set up expected output
      X_reference = df_na.copy()
      X_reference["City"] = X_reference["City"].fillna("London")
      X_reference["Studies"] = X_reference["Studies"].fillna("Bachelor")
  
      # test fit attr and transform output
      assert imputer.imputer_dict_ == {
          "Studies": "Bachelor",
          "City": "London",
      }
      pd.testing.assert_frame_equal(X_transformed, X_reference)
  
file_path: feature_engine/tests/test_imputation/test_categorical_imputer.py
imports: import pandas
  import pytest
  from feature_engine.imputation import CategoricalImputer
label_desc: Use image node_id 4 for calling a global function with example usage: test_mode_imputation_with_multiple_variables(df_na) without return types