本文整理匯總了Python中pandas.core.nanops.nanvar方法的典型用法代碼示例。如果您正苦於以下問題：Python nanops.nanvar方法的具體用法？Python nanops.nanvar怎麽用？Python nanops.nanvar使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.core.nanops的用法示例。
在下文中一共展示了nanops.nanvar方法的10個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_var_std
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_var_std(self, float_frame_with_na, datetime_frame, float_frame,
float_string_frame):
alt = lambda x: np.var(x, ddof=1)
assert_stat_op_calc('var', alt, float_frame_with_na)
assert_stat_op_api('var', float_frame, float_string_frame)
alt = lambda x: np.std(x, ddof=1)
assert_stat_op_calc('std', alt, float_frame_with_na)
assert_stat_op_api('std', float_frame, float_string_frame)
result = datetime_frame.std(ddof=4)
expected = datetime_frame.apply(lambda x: x.std(ddof=4))
tm.assert_almost_equal(result, expected)
result = datetime_frame.var(ddof=4)
expected = datetime_frame.apply(lambda x: x.var(ddof=4))
tm.assert_almost_equal(result, expected)
arr = np.repeat(np.random.random((1, 1000)), 1000, 0)
result = nanops.nanvar(arr, axis=0)
assert not (result < 0).any()
with pd.option_context('use_bottleneck', False):
result = nanops.nanvar(arr, axis=0)
assert not (result < 0).any() 示例2: test_var_std
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_var_std(self):
alt = lambda x: np.var(x, ddof=1)
self._check_stat_op('var', alt)
alt = lambda x: np.std(x, ddof=1)
self._check_stat_op('std', alt)
result = self.tsframe.std(ddof=4)
expected = self.tsframe.apply(lambda x: x.std(ddof=4))
tm.assert_almost_equal(result, expected)
result = self.tsframe.var(ddof=4)
expected = self.tsframe.apply(lambda x: x.var(ddof=4))
tm.assert_almost_equal(result, expected)
arr = np.repeat(np.random.random((1, 1000)), 1000, 0)
result = nanops.nanvar(arr, axis=0)
assert not (result < 0).any()
with pd.option_context('use_bottleneck', False):
result = nanops.nanvar(arr, axis=0)
assert not (result < 0).any() 示例3: test_nanvar
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanvar(self, ddof):
self.check_funs(nanops.nanvar, np.var, allow_complex=False,
allow_str=False, allow_date=False,
allow_tdelta=True, allow_obj='convert', ddof=ddof) 示例4: test_nanvar_all_finite
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanvar_all_finite(self):
samples = self.samples
actual_variance = nanops.nanvar(samples)
tm.assert_almost_equal(actual_variance, self.variance,
check_less_precise=2) 示例5: test_nanvar_nans
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanvar_nans(self):
samples = np.nan * np.ones(2 * self.samples.shape[0])
samples[::2] = self.samples
actual_variance = nanops.nanvar(samples, skipna=True)
tm.assert_almost_equal(actual_variance, self.variance,
check_less_precise=2)
actual_variance = nanops.nanvar(samples, skipna=False)
tm.assert_almost_equal(actual_variance, np.nan, check_less_precise=2) 示例6: test_nanstd_nans
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanstd_nans(self):
samples = np.nan * np.ones(2 * self.samples.shape[0])
samples[::2] = self.samples
actual_std = nanops.nanstd(samples, skipna=True)
tm.assert_almost_equal(actual_std, self.variance ** 0.5,
check_less_precise=2)
actual_std = nanops.nanvar(samples, skipna=False)
tm.assert_almost_equal(actual_std, np.nan,
check_less_precise=2) 示例7: test_nanvar_axis
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanvar_axis(self):
# Generate some sample data.
samples_norm = self.samples
samples_unif = self.prng.uniform(size=samples_norm.shape[0])
samples = np.vstack([samples_norm, samples_unif])
actual_variance = nanops.nanvar(samples, axis=1)
tm.assert_almost_equal(actual_variance, np.array(
[self.variance, 1.0 / 12]), check_less_precise=2) 示例8: test_ground_truth
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_ground_truth(self):
# Test against values that were precomputed with Numpy.
samples = np.empty((4, 4))
samples[:3, :3] = np.array([[0.97303362, 0.21869576, 0.55560287
], [0.72980153, 0.03109364, 0.99155171],
[0.09317602, 0.60078248, 0.15871292]])
samples[3] = samples[:, 3] = np.nan
# Actual variances along axis=0, 1 for ddof=0, 1, 2
variance = np.array([[[0.13762259, 0.05619224, 0.11568816
], [0.20643388, 0.08428837, 0.17353224],
[0.41286776, 0.16857673, 0.34706449]],
[[0.09519783, 0.16435395, 0.05082054
], [0.14279674, 0.24653093, 0.07623082],
[0.28559348, 0.49306186, 0.15246163]]])
# Test nanvar.
for axis in range(2):
for ddof in range(3):
var = nanops.nanvar(samples, skipna=True, axis=axis, ddof=ddof)
tm.assert_almost_equal(var[:3], variance[axis, ddof])
assert np.isnan(var[3])
# Test nanstd.
for axis in range(2):
for ddof in range(3):
std = nanops.nanstd(samples, skipna=True, axis=axis, ddof=ddof)
tm.assert_almost_equal(std[:3], variance[axis, ddof] ** 0.5)
assert np.isnan(std[3]) 示例9: var
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def var(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='var')
return nanops.nanvar(self._ndarray, axis=axis, skipna=skipna,
ddof=ddof) 示例10: test_nanvar
# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nanvar [as 別名]
def test_nanvar(self):
self.check_funs_ddof(nanops.nanvar, np.var, allow_complex=False,
allow_str=False, allow_date=False,
allow_tdelta=True, allow_obj='convert')