code: def test_is_single_column_target():
      validator = TargetValidator(is_classification=True)
      validator.fit(np.array([1, 2, 3, 4]))
      assert validator.is_single_column_target()
  
      validator = TargetValidator(is_classification=True)
      validator.fit(np.array([[1, 0, 1, 0], [1, 1, 1, 1]]))
      assert not validator.is_single_column_target()
  
imports: import numpy
  import pandas
  import sklearn.datasets
  import sklearn.model_selection
  from pandas.api.types import is_bool_dtype, is_numeric_dtype
  from scipy import sparse
  from sklearn.utils.multiclass import type_of_target
  from autosklearn.data.target_validator import TargetValidator
  import pytest
label_desc: Use image node_id 14 for calling a global function with example usage: test_is_single_column_target() without return types