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# pandas.api.typing.Resampler.sem

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

  Compute standard error of the mean of groups, excluding missing values.

  For multiple groupings, the result index will be a MultiIndex.

  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:
    Series or DataFrame

      Standard error of the mean of values within each group.

  See also

  `DataFrame.sem`

    Return unbiased standard error of the mean over requested axis.

  `Series.sem`

    Return unbiased standard error of the mean over requested axis.

  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").sem()
      2023-01-01    0.577350
      2023-02-01    1.527525
      Freq: MS, dtype: float64