dask_expr._rolling.Rolling.var
dask_expr._rolling.Rolling.var¶
- Rolling.var()[source]¶
Calculate the rolling variance.
This docstring was copied from pandas.core.window.rolling.Rolling.var.
Some inconsistencies with the Dask version may exist.
- Parameters
- ddofint, default 1 (Not supported in Dask)
Delta Degrees of Freedom. The divisor used in calculations is
N - ddof
, whereN
represents the number of elements.- numeric_onlybool, default False (Not supported in Dask)
Include only float, int, boolean columns.
New in version 1.5.0.
- enginestr, default None (Not supported in Dask)
'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
New in version 1.4.0.
- engine_kwargsdict, default None (Not supported in Dask)
For
'cython'
engine, there are no acceptedengine_kwargs
For
'numba'
engine, the engine can acceptnopython
,nogil
andparallel
dictionary keys. The values must either beTrue
orFalse
. The defaultengine_kwargs
for the'numba'
engine is{'nopython': True, 'nogil': False, 'parallel': False}
New in version 1.4.0.
- Returns
- Series or DataFrame
Return type is the same as the original object with
np.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 default
ddof
of 1 used inSeries.var()
is different than 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 NaN 1 NaN 2 0.333333 3 1.000000 4 1.000000 5 1.333333 6 0.000000 dtype: float64