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# pandas.api.typing.ExponentialMovingWindow.std

ExponentialMovingWindow.std(bias=False, numeric_only=False)

  Calculate the ewm (exponential weighted moment) standard deviation.

  The weighting is controlled by the `com`, `span`, `halflife`, or `alpha` parameter specified when calling `DataFrame.ewm()` or `Series.ewm()`.

  Parameters:
    bias bool, default False

      Use a standard estimation bias correction.

    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.ewm`

    Calling ewm with Series data.

  `DataFrame.ewm`

    Calling ewm with DataFrames.

  `Series.std`

    Aggregating std for Series.

  `DataFrame.std`

    Aggregating std for DataFrame.

  Examples

      >>> ser = pd.Series([1, 2, 3, 4])
      >>> ser.ewm(alpha=0.2).std()
      0         NaN
      1    0.707107
      2    0.995893
      3    1.277320
      dtype: float64