code: def test_groupby_dropna_multi_index_dataframe_nan_in_one_group(
      dropna, tuples, outputs, nulls_fixture
  ):
      # GH 3729 this is to test that NA is in one group
      df_list = [
          ["A", "B", 12, 12, 12],
          ["A", nulls_fixture, 12.3, 233.0, 12],
          ["B", "A", 123.23, 123, 1],
          ["A", "B", 1, 1, 1.0],
      ]
      df = pd.DataFrame(df_list, columns=["a", "b", "c", "d", "e"])
      grouped = df.groupby(["a", "b"], dropna=dropna).sum()
  
      mi = pd.MultiIndex.from_tuples(tuples, names=list("ab"))
  
      # Since right now, by default MI will drop NA from levels when we create MI
      # via `from_*`, so we need to add NA for level manually afterwards.
      if not dropna:
          mi = mi.set_levels(["A", "B", np.nan], level="b")
      expected = pd.DataFrame(outputs, index=mi)
  
      tm.assert_frame_equal(grouped, expected)
  
imports: import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under10p1
  from pandas.core.dtypes.missing import na_value_for_dtype
  import pandas
  import pandas._testing
  from pandas.tests.groupby import get_groupby_method_args
label_desc: Use image node_id 1 for calling a global function with example usage: test_groupby_dropna_multi_index_dataframe_nan_in_one_group(dropna, tuples, outputs, nulls_fixture) without return types