code: def test_trainval_dataset_diff_columns():
      df, df2, _ = util_generate_second_similar_dataframe_and_expected()
      df = df.rename({"x2": "x6"}, axis=1)
      assert_that(
          calling(
              FeatureLabelCorrelationChange(
                  n_samples=None, random_state=42
              ).run
          ).with_args(
              train_dataset=Dataset(df, label="label"),
              test_dataset=Dataset(df2, label="label"),
          ),
          raises(
              DatasetValidationError,
              "train and test requires to share the same features columns",
          ),
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DatasetValidationError, DeepchecksNotSupportedError, DeepchecksValueError
  from deepchecks.tabular.checks.data_integrity import FeatureLabelCorrelation
  from deepchecks.tabular.checks.train_test_validation import FeatureLabelCorrelationChange
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 15 for calling a global function with example usage: test_trainval_dataset_diff_columns() without return types