code: def test_reductions_2d_axis0(self, data, method, min_count):
      if min_count == 1 and method not in ["sum", "prod"]:
          pytest.skip(f"min_count not relevant for {method}")
  
      arr2d = data.reshape(1, -1)
  
      kwargs = {}
      if method in ["std", "var"]:
          # pass ddof=0 so we get all-zero std instead of all-NA std
          kwargs["ddof"] = 0
      elif method in ["prod", "sum"]:
          kwargs["min_count"] = min_count
  
      try:
          result = getattr(arr2d, method)(axis=0, **kwargs)
      except Exception as err:
          try:
              getattr(data, method)()
          except Exception as err2:
              assert type(err) == type(err2)
              return
          else:
              raise AssertionError(
                  "Both reductions should raise or neither"
              )
  
      def get_reduction_result_dtype(dtype):
          # windows and 32bit builds will in some cases have int32/uint32
          #  where other builds will have int64/uint64.
          if dtype.itemsize == 8:
              return dtype
          elif dtype.kind in "ib":
              return NUMPY_INT_TO_DTYPE[np.dtype(int)]
          else:
              # i.e. dtype.kind == "u"
              return NUMPY_INT_TO_DTYPE[np.dtype("uint")]
  
      if method in ["sum", "prod"]:
          # std and var are not dtype-preserving
          expected = data
          if data.dtype.kind in "iub":
              dtype = get_reduction_result_dtype(data.dtype)
              expected = data.astype(dtype)
              assert dtype == expected.dtype
  
          if min_count == 0:
              fill_value = 1 if method == "prod" else 0
              expected = expected.fillna(fill_value)
  
          tm.assert_extension_array_equal(result, expected)
      elif method == "median":
          # std and var are not dtype-preserving
          expected = data
          tm.assert_extension_array_equal(result, expected)
      elif method in ["mean", "std", "var"]:
          if is_integer_dtype(data) or is_bool_dtype(data):
              data = data.astype("Float64")
          if method == "mean":
              tm.assert_extension_array_equal(result, data)
          else:
              tm.assert_extension_array_equal(result, data - data)
  
imports: import numpy
  import pytest
  from pandas._libs.missing import is_matching_na
  from pandas.core.dtypes.common import is_bool_dtype, is_integer_dtype
  import pandas
  import pandas._testing
  from pandas.core.arrays.integer import NUMPY_INT_TO_DTYPE
label_desc: Use image node_id 15 for calling the Dim2CompatTests obj's underlying member method code with example usage: obj.test_reductions_2d_axis0(data, method, min_count) and returns: dtype, NUMPY_INT_TO_DTYPE, NUMPY_INT_TO_DTYPE