def METHOD_NAME(setup):
    # from tensor
    raw = np.random.rand(100, 10)
    tensor = mt.tensor(raw, chunk_size=7)
    r = md.DataFrame(tensor)
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame(raw))
    r = md.DataFrame(tensor, chunk_size=13)
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame(raw))
    # from Mars dataframe
    raw = pd.DataFrame(np.random.rand(100, 10), columns=list("ABCDEFGHIJ"))
    df = md.DataFrame(raw, chunk_size=15) * 2
    r = md.DataFrame(df, num_partitions=11)
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, raw * 2)
    # from tileable dict
    raw_dict = {
        "C": np.random.choice(["u", "v", "w"], size=(100,)),
        "A": pd.Series(np.random.rand(100)),
        "B": np.random.randint(0, 10, size=(100,)),
    }
    m_dict = raw_dict.copy()
    m_dict["A"] = md.Series(m_dict["A"])
    m_dict["B"] = mt.tensor(m_dict["B"])
    r = md.DataFrame(m_dict, columns=list("ABC"))
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame(raw_dict, columns=list("ABC")))
    r = md.DataFrame({"a": [mt.tensor([1, 2, 3]).sum() + 1]})
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame({"a": [7]}))
    # from tileable list
    raw_list = [
        np.random.choice(["u", "v", "w"], size=(3,)),
        pd.Series(np.random.rand(3)),
        np.random.randint(0, 10, size=(3,)),
    ]
    m_list = raw_list.copy()
    m_list[1] = md.Series(m_list[1])
    m_list[2] = mt.tensor(m_list[2])
    r = md.DataFrame(m_list, columns=list("ABC"))
    result = r.execute(extra_config={"check_dtypes": False}).fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame(raw_list, columns=list("ABC")))
    # from raw pandas initializer
    raw = pd.DataFrame(np.random.rand(100, 10), columns=list("ABCDEFGHIJ"))
    r = md.DataFrame(raw, num_partitions=10)
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, raw)
    # from mars series
    raw_s = np.random.rand(100)
    s = md.Series(raw_s, chunk_size=20)
    r = md.DataFrame(s, num_partitions=10)
    result = r.execute().fetch()
    pd.testing.assert_frame_equal(result, pd.DataFrame(raw_s))
    # test check instance
    r = r * 2
    assert isinstance(r, md.DataFrame)