code: def sortby(self, variables, ascending=True):
          
          ds = self._to_temp_dataset().sortby(variables, ascending=ascending)
          return self._from_temp_dataset(ds)
docs: Sort object by labels or values (along an axis).
  
          Sorts the dataarray, either along specified dimensions,
          or according to values of 1-D dataarrays that share dimension
          with calling object.
  
          If the input variables are dataarrays, then the dataarrays are aligned
          (via left-join) to the calling object prior to sorting by cell values.
          NaNs are sorted to the end, following Numpy convention.
  
          If multiple sorts along the same dimension is
          given, numpy's lexsort is performed along that dimension:
          https://docs.scipy.org/doc/numpy/reference/generated/numpy.lexsort.html
          and the FIRST key in the sequence is used as the primary sort key,
          followed by the 2nd key, etc.
  
          Parameters
          ----------
          variables: str, DataArray, or list of either
              1D DataArray objects or name(s) of 1D variable(s) in
              coords whose values are used to sort this array.
          ascending: boolean, optional
              Whether to sort by ascending or descending order.
  
          Returns
          -------
          sorted: DataArray
              A new dataarray where all the specified dims are sorted by dim
              labels.
  
          Examples
          --------
  
          >>> da = xr.DataArray(np.random.rand(5),
          ...                   coords=[pd.date_range('1/1/2000', periods=5)],
          ...                   dims='time')
          >>> da
          <xarray.DataArray (time: 5)>
          array([ 0.965471,  0.615637,  0.26532 ,  0.270962,  0.552878])
          Coordinates:
            * time     (time) datetime64[ns] 2000-01-01 2000-01-02 2000-01-03 ...
  
          >>> da.sortby(da)
          <xarray.DataArray (time: 5)>
          array([ 0.26532 ,  0.270962,  0.552878,  0.615637,  0.965471])
          Coordinates:
            * time     (time) datetime64[ns] 2000-01-03 2000-01-04 2000-01-05 ...