code: def test_categorical_int_target():
      df = pd.DataFrame(
          {"x": list(range(1000)), "y": list(range(1000))}
      )
  
      # Test for regression
      dataset = Dataset(df, label="y", label_type="regression")
      check = FeatureLabelCorrelation(random_state=42)
  
      result = check.run(dataset)
      assert_that(
          result.value, has_entries({"x": close_to(0.99, 0.01)})
      )
  
      # Test for classification
      dataset = Dataset(df, label="y", label_type="multiclass")
      check = FeatureLabelCorrelation(random_state=42)
  
      result = check.run(dataset)
      assert_that(result.value, has_entries({"x": close_to(0.0, 0.01)}))
  
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 3 for calling a global function with example usage: test_categorical_int_target() without return types