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_affiliation_counts()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_affiliation_counts_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_affiliation_counts_published()

        return stats_result
def test_impl(n):
            df1 = pd.DataFrame({'key1': np.arange(n), 'A': np.arange(n) + 1.0})
            df2 = pd.DataFrame({'key2': n - np.arange(n), 'A': n + np.arange(n) + 1.0})
            A3 = pd.concat([df1.A, df2.A])
            return A3.sum()