docs: def rolling_window(self, dim, window, window_dim, center=False,
                         fill_value=dtypes.NA):
          """
          Make a rolling_window along dim and add a new_dim to the last place.
  
          Parameters
          ----------
          dim: str
              Dimension over which to compute rolling_window
          window: int
              Window size of the rolling
          window_dim: str
              New name of the window dimension.
          center: boolean. default False.
              If True, pad fill_value for both ends. Otherwise, pad in the head
              of the axis.
          fill_value:
              value to be filled.
  
          Returns
          -------
          Variable that is a view of the original array with a added dimension of
          size w.
          The return dim: self.dims + (window_dim, )
          The return shape: self.shape + (window, )
  
          Examples
          --------
          >>> v=Variable(('a', 'b'), np.arange(8).reshape((2,4)))
          >>> v.rolling_window(x, 'b', 3, 'window_dim')
          <xarray.Variable (a: 2, b: 4, window_dim: 3)>
          array([[[nan, nan, 0], [nan, 0, 1], [0, 1, 2], [1, 2, 3]],
                 [[nan, nan, 4], [nan, 4, 5], [4, 5, 6], [5, 6, 7]]])
  
          >>> v.rolling_window(x, 'b', 3, 'window_dim', center=True)
          <xarray.Variable (a: 2, b: 4, window_dim: 3)>
          array([[[nan, 0, 1], [0, 1, 2], [1, 2, 3], [2, 3, nan]],
                 [[nan, 4, 5], [4, 5, 6], [5, 6, 7], [6, 7, nan]]])
          """
          if fill_value is dtypes.NA:  # np.nan is passed
              dtype, fill_value = dtypes.maybe_promote(self.dtype)
              array = self.astype(dtype, copy=False).data
          else:
              dtype = self.dtype
              array = self.data
  
          new_dims = self.dims + (window_dim, )
          return Variable(new_dims, duck_array_ops.rolling_window(
              array, axis=self.get_axis_num(dim), window=window,
              center=center, fill_value=fill_value))