code: def test_drift_classification_label(drifted_data_and_model):
      # Arrange
      train, test, model = drifted_data_and_model
      train = remove_label(train)
      test = remove_label(test)
      check = PredictionDrift(
          categorical_drift_method="PSI", drift_mode="prediction"
      )
  
      # Act
      result = check.run(train, test, model)
  
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "Drift score": close_to(0.78, 0.01),
                  "Method": equal_to("PSI"),
              }
          ),
      )
      assert_that(result.display, has_length(greater_than(0)))
  
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 5 for calling a global function with example usage: test_drift_classification_label(drifted_data_and_model) without return types