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Showing content from https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.std.html below:

pandas.DatetimeIndex.std — pandas 2.3.1 documentation

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')

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