pandas.core.window.rolling.Rolling.var#

Rolling.var(ddof=1,numeric_only=False,engine=None,engine_kwargs=None)[source]#

Calculate the rolling variance.

Parameters:

ddofint, default 1

Delta Degrees of Freedom. The divisor used in calculationsisN-ddof, whereN represents the number of elements.

numeric_onlybool, default False

Include only float, int, boolean columns.

Added in version 1.5.0.

enginestr, default None

• '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_numba

  Added in version 1.4.0.

engine_kwargsdict, default None

• For'cython' engine, there are no acceptedengine_kwargs

• For'numba' engine, the engine can acceptnopython,nogilandparallel dictionary keys. The values must either beTrue orFalse. The defaultengine_kwargs for the'numba' engine is{'nopython':True,'nogil':False,'parallel':False}

  Added in version 1.4.0.

Returns:

Series or DataFrame

Return type is the same as the original object withnp.float64 dtype.

See also

numpy.var

Equivalent method for NumPy array.

pandas.Series.rolling

Calling rolling with Series data.

pandas.DataFrame.rolling

Calling rolling with DataFrames.

pandas.Series.var

Aggregating var for Series.

pandas.DataFrame.var

Aggregating var for DataFrame.

Notes

The defaultddof of 1 used inSeries.var() is differentthan the defaultddof of 0 innumpy.var().

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).var()0         NaN1         NaN2    0.3333333    1.0000004    1.0000005    1.3333336    0.000000dtype: float64