code: def test_transform_raises_error_if_df_contains_na(df_enc, df_enc_na):
      # test case 4: when dataset contains na, transform method
      with pytest.raises(ValueError):
          encoder = DecisionTreeEncoder()
          encoder.fit(df_enc[["var_A", "var_B"]], df_enc["target"])
          encoder.transform(df_enc_na)
  
file_path: feature_engine/tests/test_encoding/test_decision_tree_encoder.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.encoding import DecisionTreeEncoder
label_desc: Use image node_id 6 for calling a global function with example usage: test_transform_raises_error_if_df_contains_na(df_enc, df_enc_na) without return types