xorbits.pandas.window.Rolling.std#
- Rolling.std(ddof=1, *args, **kwargs)[source]#
Calculate the rolling standard deviation.
- Parameters
ddof (int, default 1) – Delta Degrees of Freedom. The divisor used in calculations is
N - ddof, whereNrepresents the number of elements.numeric_only (bool, default False (Not supported yet)) –
Include only float, int, boolean columns.
New in version 1.5.0.
*args –
For NumPy compatibility and will not have an effect on the result.
Deprecated since version 1.5.0.
engine (str, default None (Not supported yet)) –
'cython': Runs the operation through C-extensions from cython.'numba': Runs the operation through JIT compiled code from numba.None: Defaults to'cython'or globally settingcompute.use_numbaNew in version 1.4.0.
engine_kwargs (dict, default None (Not supported yet)) –
For
'cython'engine, there are no acceptedengine_kwargsFor
'numba'engine, the engine can acceptnopython,nogilandparalleldictionary keys. The values must either beTrueorFalse. The defaultengine_kwargsfor the'numba'engine is{'nopython': True, 'nogil': False, 'parallel': False}New in version 1.4.0.
**kwargs –
For NumPy compatibility and will not have an effect on the result.
Deprecated since version 1.5.0.
- Returns
Return type is the same as the original object with
np.float64dtype.- Return type
See also
numpy.stdEquivalent method for NumPy array.
pandas.Series.rollingCalling rolling with Series data.
pandas.DataFrame.rollingCalling rolling with DataFrames.
pandas.Series.stdAggregating std for Series.
pandas.DataFrame.stdAggregating std for DataFrame.
Notes
The default
ddofof 1 used inSeries.std()is different than the defaultddofof 0 innumpy.std().A minimum of one period is required for the rolling calculation.
Examples
>>> s = pd.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.rolling(3).std() 0 NaN 1 NaN 2 0.577350 3 1.000000 4 1.000000 5 1.154701 6 0.000000 dtype: float64
This docstring was copied from pandas.core.window.rolling.Rolling.