# Buggy code
def _calc_axis_splits(left_axis, right_axis, left_axis_chunks, right_axis_chunks):
    if _axis_need_shuffle(left_axis, right_axis, left_axis_chunks, right_axis_chunks):
        # do shuffle
        out_chunk_size = max(len(left_axis_chunks), len(right_axis_chunks))
        return None, [np.nan for _ in range(out_chunk_size)]
    else:
        # no need to do shuffle on this axis
        left_chunk_index_min_max, left_increase = _get_chunk_index_min_max(
            left_axis, left_axis_chunks
        )
        right_chunk_index_min_max, right_increase = _get_chunk_index_min_max(
            right_axis, right_axis_chunks
        )
        if len(left_chunk_index_min_max) == 1 and len(right_chunk_index_min_max) == 1:
            # both left and right has only 1 chunk
            left_splits, right_splits = (
                [left_chunk_index_min_max],
                [right_chunk_index_min_max],
            )
        else:
            left_splits, right_splits = split_monotonic_index_min_max(
                left_chunk_index_min_max,
                left_increase,
                right_chunk_index_min_max,
                right_increase,
            )
        splits = _AxisMinMaxSplitInfo(
            left_splits, left_increase, right_splits, right_increase
        )
        nsplits = [np.nan for _ in itertools.chain(*left_splits)]
        return splits, nsplits


# 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 _calc_axis_splits(left_axis, right_axis, left_axis_chunks, right_axis_chunks):
    if _axis_need_shuffle(left_axis, right_axis, left_axis_chunks, right_axis_chunks):
        # do shuffle
        out_chunk_size = max(len(left_axis_chunks), len(right_axis_chunks))
        return None, [np.nan for _ in range(out_chunk_size)]
    else:
        # no need to do shuffle on this axis
        if _is_index_identical(left_axis_chunks, right_axis_chunks):
            left_chunk_index_min_max = _get_chunk_index_min_max(left_axis_chunks)
            right_splits = left_splits = [[c] for c in left_chunk_index_min_max]
            right_increase = left_increase = None
        elif len(left_axis_chunks) == 1 and len(right_axis_chunks) == 1:
            left_splits = [_get_chunk_index_min_max(left_axis_chunks)]
            left_increase = left_axis_chunks[0].is_monotonic_decreasing
            right_splits = [_get_chunk_index_min_max(right_axis_chunks)]
            right_increase = right_axis_chunks[0].is_monotonic_decreasing
        else:
            left_chunk_index_min_max, left_increase = (
                _get_monotonic_chunk_index_min_max(left_axis, left_axis_chunks)
            )
            right_chunk_index_min_max, right_increase = (
                _get_monotonic_chunk_index_min_max(right_axis, right_axis_chunks)
            )
            left_splits, right_splits = split_monotonic_index_min_max(
                left_chunk_index_min_max,
                left_increase,
                right_chunk_index_min_max,
                right_increase,
            )
        splits = _AxisMinMaxSplitInfo(
            left_splits, left_increase, right_splits, right_increase
        )
        nsplits = [np.nan for _ in itertools.chain(*left_splits)]
        return splits, nsplits