code: def test_df_where_with_category(self, kwargs):
      # GH#16979
      data = np.arange(2 * 3, dtype=np.int64).reshape(2, 3)
      df = DataFrame(data, columns=list("ABC"))
      mask = np.array([[True, False, False], [False, False, True]])
  
      # change type to category
      df.A = df.A.astype("category")
      df.B = df.B.astype("category")
      df.C = df.C.astype("category")
  
      result = df.where(mask, **kwargs)
      A = pd.Categorical([0, np.nan], categories=[0, 3])
      B = pd.Categorical([np.nan, np.nan], categories=[1, 4])
      C = pd.Categorical([np.nan, 5], categories=[2, 5])
      expected = DataFrame({"A": A, "B": B, "C": C})
  
      tm.assert_frame_equal(result, expected)
  
      # Check Series.where while we're here
      result = df.A.where(mask[:, 0], **kwargs)
      expected = Series(A, name="A")
  
      tm.assert_series_equal(result, expected)
  
imports: from datetime import datetime
  from hypothesis import given
  import numpy
  import pytest
  from pandas.core.dtypes.common import is_scalar
  import pandas
  from pandas import DataFrame, DatetimeIndex, Index, Series, StringDtype, Timestamp, date_range, isna
  import pandas._testing
  from pandas._testing._hypothesis import OPTIONAL_ONE_OF_ALL
label_desc: Use image node_id 26 for calling the TestDataFrameIndexingWhere obj's underlying member method code with example usage: obj.test_df_where_with_category(kwargs) without return types