code: def test_drift_not_enough_samples(drifted_data_and_model):
      # Arrange
      train, test, model = drifted_data_and_model
      train = remove_label(train)
      test = remove_label(test)
      check = PredictionDrift(min_samples=1000000)
  
      # Assert
      assert_that(
          calling(check.run).with_args(train, test, model),
          raises(NotEnoughSamplesError),
      )
  
imports: import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DeepchecksValueError, NotEnoughSamplesError
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.checks import PredictionDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 6 for calling a global function with example usage: test_drift_not_enough_samples(drifted_data_and_model) without return types