def test_sem(self, datetime_frame):
result = datetime_frame.sem(ddof=4)
expected = datetime_frame.apply(lambda x: x.std(ddof=4) / np.sqrt(len(x)))
tm.assert_almost_equal(result, expected)
arr = np.repeat(np.random.random((1, 1000)), 1000, 0)
result = nanops.nansem(arr, axis=0)
assert not (result < 0).any()
with pd.option_context("use_bottleneck", False):
result = nanops.nansem(arr, axis=0)
assert not (result < 0).any()
def sem(self, axis=None, dtype=None, out=None, ddof=1, keepdims=False,
skipna=True):
nv.validate_stat_ddof_func((), dict(dtype=dtype, out=out,
keepdims=keepdims),
fname='sem')
return nanops.nansem(self._ndarray, axis=axis, skipna=skipna,
ddof=ddof)
def sem(
self, *, axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True
):
nv.validate_stat_ddof_func(
(), dict(dtype=dtype, out=out, keepdims=keepdims), fname="sem"
)
return nanops.nansem(self._ndarray, axis=axis, skipna=skipna, ddof=ddof)
def sem(
self, *, axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True
):
nv.validate_stat_ddof_func(
(), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="sem"
)
result = nanops.nansem(self._ndarray, axis=axis, skipna=skipna, ddof=ddof)
return self._wrap_reduction_result(axis, result)
