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# pandas.DatetimeIndex.std

DatetimeIndex.std(*args, **kwargs)

  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')