code: def test_transform_dataframe_exception_when_transformer_is_ColumnTransformer_and_inverse_transform_is_true():
      """
      Test that transform_dataframe raise exception when transformer is ColumnTransformer
      and argument inverse_transform is True.
      """
      df_input = pd.DataFrame(
          {
              "col_1": [7.5, 24.4, 60.3, 57.3, 50.7, 41.4, 87.2, 47.4],
              "col_2": ["a", "a", "a", "a", "b", "b", "b", "b"],
          }
      )
      transformer = ColumnTransformer(
          [
              ("scale", StandardScaler(), ["col_1"]),
              ("onehot", OneHotEncoder(), ["col_2"]),
          ],
          remainder="passthrough",
          verbose_feature_names_out=False,
      )
  
      err_msg = re.escape(
          "`inverse_transform` is not available when using ColumnTransformers."
      )
      with pytest.raises(Exception, match=err_msg):
          transform_dataframe(
              df=df_input,
              transformer=transformer,
              fit=True,
              inverse_transform=True,
          )
  
file_path: skforecast/skforecast/utils/tests/test_transform_dataframe.py
imports: import re
  import pytest
  import re
  import numpy
  import pandas
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from skforecast.utils import transform_dataframe
label_desc: Use image node_id 2 for calling a global function with example usage: test_transform_dataframe_exception_when_transformer_is_ColumnTransformer_and_inverse_transform_is_true() without return types