code: def test_unsupported_dataframe_sparse():
      df = pd.DataFrame(
          {"A": pd.Series(pd.arrays.SparseArray(np.random.randn(10)))}
      )
      validator = FeatureValidator()
      with pytest.raises(
          ValueError,
          match=r"Auto-sklearn does not yet support sparse pandas",
      ):
          validator.fit(df)
  
imports: import numpy
  import pandas
  import sklearn.datasets
  import sklearn.model_selection
  from pandas.api.types import is_categorical_dtype, is_numeric_dtype, is_string_dtype
  from scipy import sparse
  from autosklearn.data.feature_validator import FeatureValidator
  import pytest
label_desc: Use image node_id 11 for calling a global function with example usage: test_unsupported_dataframe_sparse() without return types