modin.pandas.DatetimeIndex.std

DatetimeIndex.std(axis: AxisInt | None = None, ddof: int = 1, skipna: bool = True, **kwargs) → timedelta[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/src/snowflake/snowpark/modin/plugin/extensions/datetime_index.py#L1548-L1612)

Return sample standard deviation over requested axis.

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

Parameters:

  • axis (int, optional) – The axis to calculate the standard deviation over. This parameter is ignored - 0 is the only valid axis.

  • ddof (int, default 1) – Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. This parameter is not yet supported.

  • skipna (bool, default True) – Exclude NA/null values. If an entire row/column is NA, the result will be NA.

Return type:

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=None)
>>> idx.std()
Timedelta('1 days 00:00:00')
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