pandas.DatetimeIndex.std#

DatetimeIndex.std(axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True)[source]#

Return sample standard deviation over requested axis.

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

Parameters:

axisint, optional: Axis for the function to be applied on.
dtypeNone: Unused; for compatibility with numpy.std().
outNone: Not supported; for compatibility with numpy.std().
ddofint, default 1: Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.
keepdimsbool, default False: Not supported; for compatibility with numpy.std().
skipnabool, default True: Exclude NA/null values.

Returns:

Timedelta: Standard deviation over requested axis.

See also

numpy.ndarray.std: Returns the standard deviation of the array elements along given axis.
Series.std: Return sample standard deviation over requested axis.

Examples

>>> idx = pd.date_range("2001-01-01 00:00", periods=3)
>>> idx
DatetimeIndex(['2001-01-01', '2001-01-02', '2001-01-03'],
              dtype='datetime64[us]', freq='D')
>>> idx.std()
Timedelta('1 days 00:00:00')