def get_stats_result(self, request):
        """Return the StatsResult object for this statistic"""
        stats_datasets = StatsMakerDataverses(**request.GET.dict())

        pub_state = self.get_pub_state(request)

        if pub_state == self.PUB_STATE_ALL:
            stats_result = stats_datasets.get_dataverse_counts_by_month()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_counts_by_month_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_counts_by_month_published()

        return stats_result
def range(cls, dataset, dimension):
        dimension = dataset.get_dimension(dimension, strict=True)
        column = dataset.data[dimension.name]
        if dimension.nodata is not None:
            column = cls.replace_value(column, dimension.nodata)
        if column.dtype.kind == 'O':
            return np.NaN, np.NaN
        else:
            return finite_range(column, column.min(), column.max())