# Buggy code
def execute(cls, ctx, op):
    if len(op.inputs) == 2:
        df, other = ctx[op.inputs[0].key], ctx[op.inputs[1].key]
        if isinstance(op.inputs[0], SERIES_CHUNK_TYPE) and isinstance(
            op.inputs[1], DATAFRAME_CHUNK_TYPE
        ):
            df, other = other, df
            func_name = getattr(cls, "_rfunc_name")
        else:
            func_name = getattr(cls, "_func_name")
    elif pd.api.types.is_scalar(op.lhs) or isinstance(op.lhs, np.ndarray):
        df = ctx[op.rhs.key]
        other = op.lhs
        func_name = getattr(cls, "_rfunc_name")
    else:
        df = ctx[op.lhs.key]
        other = op.rhs
        func_name = getattr(cls, "_func_name")
    if df.ndim == 2:
        kw = dict({"axis": op.axis})
    else:
        kw = dict()
    if op.fill_value is not None:
        # comparison function like eq does not have `fill_value`
        kw["fill_value"] = op.fill_value
    if op.level is not None:
        # logical function like and may don't have `level` (for Series type)
        kw["level"] = op.level
    ctx[op.outputs[0].key] = getattr(df, func_name)(other, **kw)


# Traceback (IndexError)
In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...:                                     'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) &amp; (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most recent call last):
File "/Users/qinxuye/miniconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-10-d9c9c3710287>", line 1, in <module>
df[(df['c'] > md.to_datetime('2020-08-01')) &amp; (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
File "/Users/qinxuye/Workspace/mars/mars/core.py", line 640, in execute
return run()
File "/Users/qinxuye/Workspace/mars/mars/core.py", line 636, in run
self.data.execute(session, **kw)
File "/Users/qinxuye/Workspace/mars/mars/core.py", line 376, in execute
return run()
File "/Users/qinxuye/Workspace/mars/mars/core.py", line 371, in run
session.run(self, **kw)
File "/Users/qinxuye/Workspace/mars/mars/session.py", line 500, in run
result = self._sess.run(*tileables, **kw)
File "/Users/qinxuye/Workspace/mars/mars/session.py", line 108, in run
res = self._executor.execute_tileables(tileables, **kw)
File "/Users/qinxuye/Workspace/mars/mars/utils.py", line 439, in _inner
return func(*args, **kwargs)
File "/Users/qinxuye/Workspace/mars/mars/executor.py", line 861, in execute_tileables
tileables, tileable_graph=tileable_graph)
File "/Users/qinxuye/Workspace/mars/mars/utils.py", line 439, in _inner
return func(*args, **kwargs)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 348, in build
tileables, tileable_graph=tileable_graph)
File "/Users/qinxuye/Workspace/mars/mars/utils.py", line 439, in _inner
return func(*args, **kwargs)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 262, in build
self._on_tile_failure(tileable_data.op, exc_info)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 301, in inner
raise exc_info[1].with_traceback(exc_info[2]) from None
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 242, in build
tiled = self._tile(tileable_data, tileable_graph)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 337, in _tile
return super()._tile(tileable_data, tileable_graph)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 201, in _tile
tds[0]._inplace_tile()
File "/Users/qinxuye/Workspace/mars/mars/core.py", line 165, in _inplace_tile
return handler.inplace_tile(self)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 136, in inplace_tile
dispatched = self.dispatch(to_tile.op)
File "/Users/qinxuye/Workspace/mars/mars/utils.py", line 439, in _inner
return func(*args, **kwargs)
File "/Users/qinxuye/Workspace/mars/mars/tiles.py", line 119, in dispatch
tiled = op_cls.tile(op)
File "/Users/qinxuye/Workspace/mars/mars/dataframe/arithmetic/core.py", line 261, in tile
return cls._tile_with_tensor(op)
File "/Users/qinxuye/Workspace/mars/mars/dataframe/arithmetic/core.py", line 216, in _tile_with_tensor
rechunk_size = other.nsplits[1] if op.axis == 'columns' or op.axis == 1 else other.nsplits[0]
IndexError: tuple index out of range

# Fixed code
def execute(cls, ctx, op):
    if len(op.inputs) == 2:
        df, other = ctx[op.inputs[0].key], ctx[op.inputs[1].key]
        if isinstance(op.inputs[0], SERIES_CHUNK_TYPE) and isinstance(
            op.inputs[1], DATAFRAME_CHUNK_TYPE
        ):
            df, other = other, df
            func_name = getattr(cls, "_rfunc_name")
        else:
            func_name = getattr(cls, "_func_name")
    elif pd.api.types.is_scalar(op.lhs) or isinstance(op.lhs, np.ndarray):
        df = ctx[op.rhs.key]
        other = op.lhs
        func_name = getattr(cls, "_rfunc_name")
    else:
        df = ctx[op.lhs.key]
        other = op.rhs
        func_name = getattr(cls, "_func_name")
    if df.ndim == 2:
        kw = dict({"axis": op.axis})
    else:
        kw = dict()
    if op.fill_value is not None:
        # comparison function like eq does not have `fill_value`
        kw["fill_value"] = op.fill_value
    if op.level is not None:
        # logical function like and may don't have `level` (for Series type)
        kw["level"] = op.level
    if hasattr(other, "ndim") and other.ndim == 0:
        other = other.item()
    ctx[op.outputs[0].key] = getattr(df, func_name)(other, **kw)