code: def test_perturbator():
      test_df = pd.DataFrame(
          {"a": [1, 1, 0], "bb": [2, 0, 0], "target": [0, 1, 2]}
      )
  
      expected_df = pd.DataFrame(
          {
              "a": [np.nan, np.nan, np.nan],
              "bb": [2, 0, 0],
              "target": [0, 1, 2],
          }
      )
  
      out_df = perturbator(
          data=test_df, cols=["a"], corruption_fn=nullify()
      )
  
      assert expected_df.equals(out_df)
  
file_path: fklearn/tests/validation/test_perturbators.py
imports: from fklearn.validation.perturbators import shift_mu, random_noise, nullify, sample_columns, perturbator
  import pandas
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: test_perturbator() without return types