code: def test_series_agg_with_min_count(method, min_count):
      df = pd.DataFrame([[1]], columns=["a"])
      ddf = dd.from_pandas(df, npartitions=1)
      func = getattr(ddf["a"], method)
      result = func(min_count=min_count).compute()
      if min_count == 0:
          assert result == 1
      else:
          assert result is np.nan
  
imports: from __future__ import annotations
  import contextlib
  import warnings
  from datetime import datetime
  import numpy
  import pandas
  import pytest
  from pandas.api.types import is_scalar
  import dask.dataframe
  from dask.array.numpy_compat import _numpy_125
  from dask.dataframe._compat import PANDAS_GE_140, PANDAS_GE_150, PANDAS_GE_200, PANDAS_VERSION, check_numeric_only_deprecation
  from dask.dataframe.utils import assert_dask_graph, assert_eq, make_meta, pyarrow_strings_enabled
label_desc: Use image node_id 29 for calling a global function with example usage: test_series_agg_with_min_count(method, min_count) without return types