Class Shift

dask/dataframe/dask_expr/_expr.py:3454–3495

class Shift(MapOverlap):
    _parameters = ["frame", "periods", "freq"]
    _defaults = {"periods": 1, "freq": None}

    func = M.shift
    enforce_metadata = True
    transform_divisions = False
    align_dataframes = True

    @functools.cached_property
    def clear_divisions(self):
        # TODO We can do better if freq is given, but this needs adjustments in
        #  map_partitions
        return True if self._divisions()[0] is None or self.freq is not None else False

    def _divisions(self):
        if self.freq is None:
            return self.frame.divisions
        divisions = _calc_maybe_new_divisions(self.frame, self.periods, self.freq)
        if divisions is None:
            divisions = (None,) * (self.frame.npartitions + 1)
        return divisions

    @functools.cached_property
    def _meta(self):
        return make_meta(meta_nonempty(self.frame._meta).shift(**self.kwargs))

    @functools.cached_property
    def kwargs(self):
        return dict(periods=self.periods, freq=self.freq)

    def _simplify_up(self, parent, dependents):
        if isinstance(parent, Projection):
            return plain_column_projection(self, parent, dependents)

    @property
    def before(self):
        return max(0, self.periods)

    @property
    def after(self):
        return 0 if self.periods > 0 else -self.periods


class ShiftIndex(Blockwise):