Skip to main content
`Ctrl`+`K`

# pandas.api.typing.Resampler.std

final Resampler.std(ddof=1, numeric_only=False)

  Compute standard deviation of groups, excluding missing values.

  This method calculates the sample standard deviation of values within each resampled time period.

  Parameters:
    ddof int, default 1

      Degrees of freedom.

    numeric_only bool, default False

      Include only float, int or boolean data.

      Changed in version 2.0.0: numeric_only now defaults to `False`.

  Returns:
    DataFrame or Series

      Standard deviation of values within each group.

  See also

  `core.resample.Resampler.mean`

    Compute mean of groups, excluding missing values.

  `core.resample.Resampler.median`

    Compute median of groups, excluding missing values.

  `core.resample.Resampler.var`

    Compute variance of groups, excluding missing values.

  Notes

  To use the same divisor as `numpy.std`, use `ddof=0` instead of the default `ddof=1`.

  Examples

      >>> ser = pd.Series(
      ...     [1, 3, 2, 4, 3, 8],
      ...     index=pd.DatetimeIndex(
      ...         [
      ...             "2023-01-01",
      ...             "2023-01-10",
      ...             "2023-01-15",
      ...             "2023-02-01",
      ...             "2023-02-10",
      ...             "2023-02-15",
      ...         ]
      ...     ),
      ... )
      >>> ser.resample("MS").std()
      2023-01-01    1.000000
      2023-02-01    2.645751
      Freq: MS, dtype: float64