code: def test_comprehensive_transform():
      y = load_airline()
      # Test that prior test also works when Index is converted to DateTime index
      y.index = y.index.to_timestamp().astype("datetime64[ns]")
      y_train, y_test = temporal_train_test_split(y)
      pipe = DateTimeFeatures(
          ts_freq="L",
          feature_scope="comprehensive",
          keep_original_columns=True,
      )
      y_train_t = pipe.fit_transform(y_train)
      return y_train_t
  
imports: import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from sktime.datasets import load_airline, load_longley, load_PBS_dataset
  from sktime.split import temporal_train_test_split
  from sktime.tests.test_switch import run_test_for_class
  from sktime.transformations.series.date import DateTimeFeatures
  from sktime.utils._testing.hierarchical import _make_hierarchical
label_desc: Use image node_id 17 for calling a global function with example usage: test_comprehensive_transform() and returns: y_train_t