def skew(self, **kwargs) -> Self:
        """
        Return a deterministic ``TimeSeries`` containing the skew of each component
        (over the samples) of this stochastic ``TimeSeries``.

        This works only on stochastic series (i.e., with more than 1 sample)

        Parameters
        ----------
        kwargs
            Other keyword arguments are passed down to `scipy.stats.skew()`

        Returns
        -------
        TimeSeries
            The TimeSeries containing the skew for each component.
        """
        self._assert_stochastic()
        new_data = np.expand_dims(skew(self._xa.values, axis=2, **kwargs), axis=2)
        new_xa = xr.DataArray(
            new_data, dims=self._xa.dims, coords=self._xa.coords, attrs=self._xa.attrs
        )
        return self.__class__(new_xa)

        Return a deterministic ``TimeSeries`` containing the skew of each component
        (over the samples) of this stochastic ``TimeSeries``.

        This works only on stochastic series (i.e., with more than 1 sample)

        Parameters
        ----------
        kwargs
            Other keyword arguments are passed down to `scipy.stats.skew()`

        Returns
        -------
        TimeSeries
            The TimeSeries containing the skew for each component.
        
darts/timeseries.py