def test_drop_obs_column():
    adata = ad.AnnData(np.array(X_list), obs=obs_dict, dtype="int32")

    subset = adata[:2]
    assert subset.is_view
    # returns a copy of obs
    assert subset.obs.drop(columns=["oanno1"]).columns.tolist() == ["oanno2", "oanno3"]
    assert subset.is_view
    # would modify obs, so it should actualize subset and not modify adata
    subset.obs.drop(columns=["oanno1"], inplace=True)
    assert not subset.is_view
    assert subset.obs.columns.tolist() == ["oanno2", "oanno3"]

    assert adata.obs.columns.tolist() == ["oanno1", "oanno2", "oanno3"]
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