def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def test_impl(A, B):
            df = pd.DataFrame({'A': A, 'B': B})
            df2 = df.groupby('A', as_index=False)['B'].sum()
            # TODO: fix handling of df setitem to force match of array dists
            # probably with a new node that is appended to the end of basic block
            # df2['C'] = np.full(len(df2.B), 3, np.int8)
            # TODO: full_like for Series
            df2['C'] = np.full_like(df2.B.values, 3, np.int8)
            return df2