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# pandas.api.typing.Rolling.sem

Rolling.sem(ddof=1, numeric_only=False)

  Calculate the rolling standard error of mean.

  This is computed as the rolling standard deviation divided by the square root of the rolling count. A minimum of one period is required.

  Parameters:
    ddof int, default 1

      Delta Degrees of Freedom. The divisor used in calculations is `N - ddof`, where `N` represents the number of elements.

    numeric_only bool, default False

      Include only float, int, boolean columns.

  Returns:
    Series or DataFrame

      Return type is the same as the original object with `np.float64` dtype.

  See also

  `Series.rolling`

    Calling rolling with Series data.

  `DataFrame.rolling`

    Calling rolling with DataFrames.

  `Series.sem`

    Aggregating sem for Series.

  `DataFrame.sem`

    Aggregating sem for DataFrame.

  Notes

  A minimum of one period is required for the calculation.

  Examples

      >>> s = pd.Series([0, 1, 2, 3])
      >>> s.rolling(2, min_periods=1).sem()
      0    NaN
      1    0.5
      2    0.5
      3    0.5
      dtype: float64