# Buggy code
def build_concated_rows_frame(df):
    from .operands import ObjectType
    from .merge.concat import DataFrameConcat

    # When the df isn't splitted along the column axis, return the df directly.
    if df.chunk_shape[1] == 1:
        return df

    columns = concat_index_value(
        [df.cix[0, idx].columns for idx in range(df.chunk_shape[1])], store_data=True
    )
    columns_size = columns.to_pandas().size

    out_chunks = []
    for idx in range(df.chunk_shape[0]):
        out_chunk = DataFrameConcat(axis=1, object_type=ObjectType.dataframe).new_chunk(
            [df.cix[idx, k] for k in range(df.chunk_shape[1])],
            index=(idx, 0),
            shape=(df.cix[idx, 0].shape[0], columns_size),
            dtypes=df.dtypes,
            index_value=df.cix[idx, 0].index_value,
            columns_value=columns,
        )
        out_chunks.append(out_chunk)

    return DataFrameConcat(axis=1, object_type=ObjectType.dataframe).new_dataframe(
        [df],
        chunks=out_chunks,
        nsplits=((chunk.shape[0] for chunk in out_chunks), (df.shape[1],)),
        shape=df.shape,
        dtypes=df.dtypes,
        index_value=df.index_value,
        columns_value=df.columns,
    )


# Traceback (Exception)
In [28]: df = md.DataFrame(np.random.rand(10, 2))

In [29]: df + np.random.rand(10, 2)
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-29-4a212df011a8> in <module>
----> 1 df + np.random.rand(10, 2)

~/Documents/mars_dev/mars/mars/dataframe/utils.py in wrapper(*args, **kwargs)
613     def wrapper(*args, **kwargs):
614         try:
--> 615             return func(*args, **kwargs)
616         except NotImplementedError:
617             return NotImplemented

~/Documents/mars_dev/mars/mars/dataframe/arithmetic/add.py in add(df, other, axis, level, fill_value)
33
34 def add(df, other, axis='columns', level=None, fill_value=None):
---> 35     other = wrap_sequence(other)
36     op = DataFrameAdd(axis=axis, level=level, fill_value=fill_value, lhs=df, rhs=other)
37     return op(df, other)

~/Documents/mars_dev/mars/mars/dataframe/utils.py in wrap_sequence(seq)
606
607     if isinstance(seq, (list, tuple, np.ndarray, TENSOR_TYPE)):
--> 608         seq = Series(seq)
609     return seq
610

~/Documents/mars_dev/mars/mars/dataframe/initializer.py in __init__(self, data, index, dtype, name, copy, chunk_size, gpu, sparse)
46             series = data
47         else:
---> 48             pd_series = pd.Series(data, index=index, dtype=dtype, name=name, copy=copy)
49             series = from_pandas_series(pd_series, chunk_size=chunk_size, gpu=gpu, sparse=sparse)
50         super(Series, self).__init__(series.data)

~/miniconda3/lib/python3.7/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
312                     data = data.copy()
313             else:
--> 314                 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
315
316                 data = SingleBlockManager(data, index, fastpath=True)

~/miniconda3/lib/python3.7/site-packages/pandas/core/internals/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
727     elif subarr.ndim > 1:
728         if isinstance(data, np.ndarray):
--> 729             raise Exception("Data must be 1-dimensional")
730         else:
731             subarr = com.asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional

# Fixed code
def build_concated_rows_frame(df):
    from .operands import ObjectType
    from .merge.concat import DataFrameConcat

    # When the df isn't splitted along the column axis, return the df directly.
    if df.chunk_shape[1] == 1:
        return df

    columns = concat_index_value(
        [df.cix[0, idx].columns_value for idx in range(df.chunk_shape[1])],
        store_data=True,
    )
    columns_size = columns.to_pandas().size

    out_chunks = []
    for idx in range(df.chunk_shape[0]):
        out_chunk = DataFrameConcat(axis=1, object_type=ObjectType.dataframe).new_chunk(
            [df.cix[idx, k] for k in range(df.chunk_shape[1])],
            index=(idx, 0),
            shape=(df.cix[idx, 0].shape[0], columns_size),
            dtypes=df.dtypes,
            index_value=df.cix[idx, 0].index_value,
            columns_value=columns,
        )
        out_chunks.append(out_chunk)

    return DataFrameConcat(axis=1, object_type=ObjectType.dataframe).new_dataframe(
        [df],
        chunks=out_chunks,
        nsplits=((chunk.shape[0] for chunk in out_chunks), (df.shape[1],)),
        shape=df.shape,
        dtypes=df.dtypes,
        index_value=df.index_value,
        columns_value=df.columns_value,
    )