pandas.core.window.Expanding.std

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

Calculate expanding standard deviation.

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

Parameters:	ddof : int, 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 expanding calculation.

See also

Series.expanding

Calling object with Series data

DataFrame.expanding

Calling object with DataFrames

Series.std

Equivalent method for Series

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