SumTransform(WindowStatisticsTransform):
  def __init__(
        self,
        in_column: str,  # name of column to apply transformation
        window: int,  #
        seasonality: int = 1,
        min_periods: int = 1,
        fillna: float = 0,
        out_column: Optional[str] = None,
    ):
    """Init SumTransform.

        Parameters
        ----------
        in_column:
            name of processed column
        window: 
            size of window to aggregate, if window == -1 compute rolling sum all over the given series
        seasonality:
            seasonality of lags to compute window's aggregation with
        min_periods:
            min number of targets in window to compute aggregation;
            if there is less than ``min_periods`` number of targets return None
        fillna:
            value to fill results NaNs with
        out_column: 
            result column name. If not given use ``self.__repr__()``
        """