pandas.core.window.rolling.Rolling.std

Rolling.std(ddof=1, *args, **kwargs)[source]

Calculate rolling standard deviation.

Normalized by N-1 by default. This can be changed using the ddof argument.

Parameters
ddofint, default 1

Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.

*args, **kwargs

For NumPy compatibility. No additional arguments are used.

Returns
Series or DataFrame

Returns the same object type as the caller of the rolling calculation.

See also

pandas.Series.rolling

Calling object with Series data.

pandas.DataFrame.rolling

Calling object with DataFrames.

pandas.Series.std

Equivalent method for Series.

pandas.DataFrame.std

Equivalent method for DataFrame.

numpy.std

Equivalent method for Numpy array.

Notes

The default ddof of 1 used in Series.std is different than the default ddof of 0 in numpy.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

>>> s.expanding(3).std()
0         NaN
1         NaN
2    0.577350
3    0.957427
4    0.894427
5    0.836660
6    0.786796
dtype: float64
pandas.core.window.rolling.Rolling.var pandas.core.window.rolling.Rolling.min