TST: unskip EA reduction tests (#59247)

unskip more EA reduction tests

Author: lukemanley

pandas/core/arrays/masked.py

@@ -1198,7 +1198,7 @@ def _wrap_na_result(self, *, name, axis, mask_size):
  mask = np.ones(mask_size, dtype=bool)
 
  float_dtyp = "float32" if self.dtype == "Float32" else "float64"
- if name in ["mean", "median", "var", "std", "skew", "kurt"]:
+ if name in ["mean", "median", "var", "std", "skew", "kurt", "sem"]:
  np_dtype = float_dtyp
  elif name in ["min", "max"] or self.dtype.itemsize == 8:
  np_dtype = self.dtype.numpy_dtype.name

pandas/tests/extension/base/reduce.py

@@ -56,7 +56,7 @@ def check_reduce_frame(self, ser: pd.Series, op_name: str, skipna: bool):
  arr = ser.array
  df = pd.DataFrame({"a": arr})
 
- kwargs = {"ddof": 1} if op_name in ["var", "std"] else {}
+ kwargs = {"ddof": 1} if op_name in ["var", "std", "sem"] else {}
 
  cmp_dtype = self._get_expected_reduction_dtype(arr, op_name, skipna)
 
@@ -119,7 +119,7 @@ def test_reduce_frame(self, data, all_numeric_reductions, skipna):
  op_name = all_numeric_reductions
  ser = pd.Series(data)
 
- if op_name in ["count", "kurt", "sem"]:
+ if op_name == "count":
  pytest.skip(f"{op_name} not an array method")
 
  if not self._supports_reduction(ser, op_name):

pandas/tests/extension/decimal/test_decimal.py

@@ -72,6 +72,8 @@ def _get_expected_exception(
  return None
 
  def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
+ if op_name in ["kurt", "sem"]:
+ return False
  return True
 
  def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):

pandas/tests/extension/test_arrow.py

@@ -467,17 +467,14 @@ def test_accumulate_series(self, data, all_numeric_accumulations, skipna, reques
  self.check_accumulate(ser, op_name, skipna)
 
  def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
+ if op_name in ["kurt", "skew"]:
+ return False
+
  dtype = ser.dtype
  # error: Item "dtype[Any]" of "dtype[Any] | ExtensionDtype" has
  # no attribute "pyarrow_dtype"
  pa_dtype = dtype.pyarrow_dtype # type: ignore[union-attr]
- if pa.types.is_temporal(pa_dtype) and op_name in [
- "sum",
- "var",
- "skew",
- "kurt",
- "prod",
- ]:
+ if pa.types.is_temporal(pa_dtype) and op_name in ["sum", "var", "prod"]:
  if pa.types.is_duration(pa_dtype) and op_name in ["sum"]:
  # summing timedeltas is one case that *is* well-defined
  pass
@@ -493,8 +490,6 @@ def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
  "std",
  "sem",
  "var",
- "skew",
- "kurt",
  ]:
  return False
 
@@ -541,23 +536,6 @@ def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):
  expected = getattr(alt, op_name)(skipna=skipna)
  tm.assert_almost_equal(result, expected)
 
- @pytest.mark.parametrize("skipna", [True, False])
- def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna, request):
- dtype = data.dtype
- pa_dtype = dtype.pyarrow_dtype
-
- xfail_mark = pytest.mark.xfail(
- raises=TypeError,
- reason=(
- f"{all_numeric_reductions} is not implemented in "
- f"pyarrow={pa.__version__} for {pa_dtype}"
- ),
- )
- if all_numeric_reductions in {"skew", "kurt"} and dtype._is_numeric:
- request.applymarker(xfail_mark)
-
- super().test_reduce_series_numeric(data, all_numeric_reductions, skipna)
-
  @pytest.mark.parametrize("skipna", [True, False])
  def test_reduce_series_boolean(
  self, data, all_boolean_reductions, skipna, na_value, request
@@ -596,11 +574,11 @@ def _get_expected_reduction_dtype(self, arr, op_name: str, skipna: bool):
  else:
  cmp_dtype = arr.dtype
  elif arr.dtype.name == "decimal128(7, 3)[pyarrow]":
- if op_name not in ["median", "var", "std"]:
+ if op_name not in ["median", "var", "std", "sem"]:
  cmp_dtype = arr.dtype
  else:
  cmp_dtype = "float64[pyarrow]"
- elif op_name in ["median", "var", "std", "mean", "skew"]:
+ elif op_name in ["median", "var", "std", "mean", "skew", "sem"]:
  cmp_dtype = "float64[pyarrow]"
  elif op_name in ["sum", "prod"] and pa.types.is_boolean(pa_type):
  cmp_dtype = "uint64[pyarrow]"
@@ -619,7 +597,11 @@ def test_reduce_frame(self, data, all_numeric_reductions, skipna, request):
  if data.dtype._is_numeric:
  mark = pytest.mark.xfail(reason="skew not implemented")
  request.applymarker(mark)
- elif op_name == "std" and pa.types.is_date64(data._pa_array.type) and skipna:
+ elif (
+ op_name in ["std", "sem"]
+ and pa.types.is_date64(data._pa_array.type)
+ and skipna
+ ):
  # overflow
  mark = pytest.mark.xfail(reason="Cannot cast")
  request.applymarker(mark)

pandas/tests/extension/test_masked.py

@@ -301,7 +301,7 @@ def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):
  def _get_expected_reduction_dtype(self, arr, op_name: str, skipna: bool):
  if is_float_dtype(arr.dtype):
  cmp_dtype = arr.dtype.name
- elif op_name in ["mean", "median", "var", "std", "skew"]:
+ elif op_name in ["mean", "median", "var", "std", "skew", "kurt", "sem"]:
  cmp_dtype = "Float64"
  elif op_name in ["max", "min"]:
  cmp_dtype = arr.dtype.name
@@ -323,9 +323,7 @@ def _get_expected_reduction_dtype(self, arr, op_name: str, skipna: bool):
  else "UInt64"
  )
  elif arr.dtype.kind == "b":
- if op_name in ["mean", "median", "var", "std", "skew"]:
- cmp_dtype = "Float64"
- elif op_name in ["min", "max"]:
+ if op_name in ["min", "max"]:
  cmp_dtype = "boolean"
  elif op_name in ["sum", "prod"]:
  cmp_dtype = (