code: def test_value_counts_na(dtype):
      if getattr(dtype, "storage", "") == "pyarrow":
          exp_dtype = "int64[pyarrow]"
      elif getattr(dtype, "storage", "") == "pyarrow_numpy":
          exp_dtype = "int64"
      else:
          exp_dtype = "Int64"
      arr = pd.array(["a", "b", "a", pd.NA], dtype=dtype)
      result = arr.value_counts(dropna=False)
      expected = pd.Series(
          [2, 1, 1], index=arr[[0, 1, 3]], dtype=exp_dtype, name="count"
      )
      tm.assert_series_equal(result, expected)
  
      result = arr.value_counts(dropna=True)
      expected = pd.Series(
          [2, 1], index=arr[:2], dtype=exp_dtype, name="count"
      )
      tm.assert_series_equal(result, expected)
  
imports: import operator
  import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under12p0
  from pandas.core.dtypes.common import is_dtype_equal
  import pandas
  import pandas._testing
  from pandas.core.arrays.string_arrow import ArrowStringArray, ArrowStringArrayNumpySemantics
label_desc: Use image node_id 34 for calling a global function with example usage: test_value_counts_na(dtype) without return types