pandas.DatetimeIndex.std#

DatetimeIndex.std(*args, **kwargs)[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. For pandas.Series this parameter is unused and defaults to None.
ddofint, default 1: Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.
skipnabool, default True: Exclude NA/null values. If an entire row/column is NA, the result will be NA.

Returns:

Timedelta

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

For pandas.DatetimeIndex:

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