code: def test_imputers_pandas_na_integer_array_support(
      imputer, add_indicator
  ):
      # Test pandas IntegerArray with pd.NA
      pd = pytest.importorskip("pandas")
      marker = np.nan
      imputer = imputer.set_params(
          add_indicator=add_indicator, missing_values=marker
      )
  
      X = np.array(
          [
              [marker, 1, 5, marker, 1],
              [2, marker, 1, marker, 2],
              [6, 3, marker, marker, 3],
              [1, 2, 9, marker, 4],
          ]
      )
      # fit on numpy array
      X_trans_expected = imputer.fit_transform(X)
  
      # Creates dataframe with IntegerArrays with pd.NA
      X_df = pd.DataFrame(
          X, dtype="Int16", columns=["a", "b", "c", "d", "e"]
      )
  
      # fit on pandas dataframe with IntegerArrays
      X_trans = imputer.fit_transform(X_df)
  
      assert_allclose(X_trans_expected, X_trans)
  
file_path: scikit-learn/sklearn/impute/tests/test_common.py
imports: import numpy
  import pytest
  from sklearn.experimental import enable_iterative_imputer
  from sklearn.impute import IterativeImputer, KNNImputer, SimpleImputer
  from sklearn.utils._testing import assert_allclose, assert_allclose_dense_sparse, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 6 for calling a global function with example usage: test_imputers_pandas_na_integer_array_support(imputer, add_indicator) without return types