# Buggy code
def tile(cls, op):
    in_df = op.inputs[0]
    out_df = op.outputs[0]

    # See Note [Fancy Index of Numpy and Pandas]
    tensor0 = empty(in_df.shape[0], chunk_size=(in_df.nsplits[0],))[
        op.indexes[0]
    ].tiles()
    tensor1 = empty(in_df.shape[1], chunk_size=(in_df.nsplits[1],))[
        op.indexes[1]
    ].tiles()

    chunk_mapping = {
        c0.inputs[0].index + c1.inputs[0].index: (c0, c1)
        for c0, c1 in itertools.product(tensor0.chunks, tensor1.chunks)
    }

    out_chunks = []
    for chunk in in_df.chunks:
        if chunk.index not in chunk_mapping:
            out_chunks.append(chunk)
        else:
            chunk_op = op.copy().reset_key()
            index_chunk, column_chunk = chunk_mapping[chunk.index]
            chunk_op._indexes = (index_chunk.op.indexes[0], column_chunk.op.indexes[0])
            chunk_op._value = op.value
            out_chunk = chunk_op.new_chunk(
                [chunk],
                shape=chunk.shape,
                index=chunk.index,
                dtypes=chunk.dtypes,
                index_value=chunk.index_value,
                columns_value=chunk.columns,
            )
            out_chunks.append(out_chunk)

    new_op = op.copy()
    return new_op.new_dataframes(
        op.inputs,
        shape=out_df.shape,
        dtypes=out_df.dtypes,
        index_value=out_df.index_value,
        columns_value=out_df.columns,
        chunks=out_chunks,
        nsplits=in_df.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 tile(cls, op):
    in_df = op.inputs[0]
    out_df = op.outputs[0]

    # See Note [Fancy Index of Numpy and Pandas]
    tensor0 = empty(in_df.shape[0], chunk_size=(in_df.nsplits[0],))[
        op.indexes[0]
    ].tiles()
    tensor1 = empty(in_df.shape[1], chunk_size=(in_df.nsplits[1],))[
        op.indexes[1]
    ].tiles()

    chunk_mapping = {
        c0.inputs[0].index + c1.inputs[0].index: (c0, c1)
        for c0, c1 in itertools.product(tensor0.chunks, tensor1.chunks)
    }

    out_chunks = []
    for chunk in in_df.chunks:
        if chunk.index not in chunk_mapping:
            out_chunks.append(chunk)
        else:
            chunk_op = op.copy().reset_key()
            index_chunk, column_chunk = chunk_mapping[chunk.index]
            chunk_op._indexes = (index_chunk.op.indexes[0], column_chunk.op.indexes[0])
            chunk_op._value = op.value
            out_chunk = chunk_op.new_chunk(
                [chunk],
                shape=chunk.shape,
                index=chunk.index,
                dtypes=chunk.dtypes,
                index_value=chunk.index_value,
                columns_value=chunk.columns_value,
            )
            out_chunks.append(out_chunk)

    new_op = op.copy()
    return new_op.new_dataframes(
        op.inputs,
        shape=out_df.shape,
        dtypes=out_df.dtypes,
        index_value=out_df.index_value,
        columns_value=out_df.columns_value,
        chunks=out_chunks,
        nsplits=in_df.nsplits,
    )