code: def test_groupby_sum_mincount_boolean(min_count):
      b = True
      a = False
      na = np.nan
      dfg = pd.array([b, b, na, na, a, a, b], dtype="boolean")
  
      df = DataFrame({"A": [1, 1, 2, 2, 3, 3, 1], "B": dfg})
      result = df.groupby("A").sum(min_count=min_count)
      if min_count == 0:
          expected = DataFrame(
              {"B": pd.array([3, 0, 0], dtype="Int64")},
              index=pd.Index([1, 2, 3], name="A"),
          )
          tm.assert_frame_equal(result, expected)
      else:
          expected = DataFrame(
              {"B": pd.array([pd.NA] * 3, dtype="Int64")},
              index=pd.Index([1, 2, 3], name="A"),
          )
          tm.assert_frame_equal(result, expected)
  
imports: import builtins
  import datetime
  from string import ascii_lowercase
  import numpy
  import pytest
  from pandas._libs.tslibs import iNaT
  import pandas
  from pandas import DataFrame, MultiIndex, Series, Timestamp, date_range, isna
  import pandas._testing
  from pandas.util import _test_decorators
label_desc: Use image node_id 42 for calling a global function with example usage: test_groupby_sum_mincount_boolean(min_count) without return types