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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def roll(self, shifts=None, roll_coords=None, **shifts_kwargs):
 """Roll this dataset by an offset along one or more dimensions. Unlike shift, roll may rotate all variables, including coordinates if specified. The direction of rotation is consistent with :py:func:`numpy.roll`. Parameters shifts : dict, optional A dict with keys matching dimensions and values given by integers to rotate each of the given dimensions. Positive offsets roll to the right; negative offsets roll to the left. roll_coords : bool Indicates whether to roll the coordinates by the offset The current default of roll_coords (None, equivalent to True) is deprecated and will change to False in a future version. Explicitly pass roll_coords to silence the warning. The keyword arguments form of ``shifts``. One of shifts or shifts_kwargs must be provided. Returns ------- rolled : Dataset Dataset with the same coordinates and attributes but rolled variables. See also -------- shift Examples -------- <xarray.Dataset> Dimensions: (x: 5) Coordinates: * x (x) int64 3 4 0 1 2 Data variables: foo (x) object 'd' 'e' 'a' 'b' 'c' """

        shifts = either_dict_or_kwargs(shifts, shifts_kwargs, 'roll')
        invalid = [k for k in shifts if k not in self.dims]
        if invalid:
            raise ValueError("dimensions %r do not exist" % invalid)

        if roll_coords is None:
            warnings.warn("roll_coords will be set to False in the future."
                          " Explicitly set roll_coords to silence warning.",
                          FutureWarning, stacklevel=2)
            roll_coords = True

        unrolled_vars = () if roll_coords else self.coords

        variables = OrderedDict()
        for k, v in self.variables.items():
            if k not in unrolled_vars:
                variables[k] = v.roll(**{k: s for k, s in shifts.items()
                                         if k in v.dims})
            else:
                variables[k] = v

        return self._replace_vars_and_dims(variables)