# Buggy code
def size(self):
    return pandas.Series({k: len(v) for k, v in self._index_grouped.items()})


# Traceback (ray.exceptions.RayTaskError)
Traceback (most recent call last):
File "groupby_test16.py", line 29, in <module>
df1 = gb.prod()
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 333, in prod
return self._groupby_reduce(callable, None)
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 582, in _groupby_reduce
query_compiler=groupby_qc.groupby_reduce(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1298, in groupby_reduce
new_modin_frame = qc._modin_frame.groupby_reduce(
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 1259, in groupby_reduce
new_index = self._frame_mgr_cls.get_indices(
File "/localdisk/gashiman/modin/modin/engines/ray/pandas_on_ray/frame/partition_manager.py", line 87, in get_indices
new_idx = ray.get(new_idx)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/ray/worker.py", line 1515, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(ValueError): ray::modin.engines.ray.pandas_on_ray.frame.partition.deploy_ray_func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 427, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 449, in ray._raylet.execute_task
ray.exceptions.RayTaskError: ray::modin.engines.ray.pandas_on_ray.frame.axis_partition.deploy_ray_func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 427, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 449, in ray._raylet.execute_task
ray.exceptions.RayTaskError: ray::modin.engines.ray.pandas_on_ray.frame.partition_manager.func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 463, in ray._raylet.execute_task
File "/localdisk/gashiman/modin/modin/engines/ray/pandas_on_ray/frame/partition_manager.py", line 44, in func
return apply_func(df, other)
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1248, in _map
result = map_func(
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 332, in callable
return df.prod(**kwargs)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 1371, in f
return self._cython_agg_general(alias, alt=npfunc, **kwargs)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 993, in _cython_agg_general
agg_blocks, agg_items = self._cython_agg_blocks(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 1022, in _cython_agg_blocks
result, _ = self.grouper.aggregate(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 586, in aggregate
return self._cython_operation(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 529, in _cython_operation
result = self._aggregate(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 608, in _aggregate
agg_func(result, counts, values, comp_ids, min_count)
File "pandas/_libs/groupby.pyx", line 511, in pandas._libs.groupby._group_prod
File "stringsource", line 658, in View.MemoryView.memoryview_cwrapper
File "stringsource", line 349, in View.MemoryView.memoryview.__cinit__
ValueError: buffer source array is read-only

# Fixed code
def size(self):
    if self._axis == 0:
        if self._as_index:
            work_object = self[self._df.columns[0]]
        else:
            # Size always works in as_index=True mode so it is necessary to make a copy
            # of _kwargs and change as_index in it
            kwargs = self._kwargs.copy()
            kwargs["as_index"] = True
            kwargs["squeeze"] = True
            work_object = SeriesGroupBy(
                self._df[self._df.columns[0]],
                self._by,
                self._axis,
                idx_name=self._idx_name,
                drop=False,
                **kwargs,
            )

        result = work_object._groupby_reduce(
            lambda df: pandas.DataFrame(df.size()),
            lambda df: df.sum(),
            numeric_only=False,
        )
        series_result = Series(query_compiler=result._query_compiler)
        # Pandas does not name size() output
        series_result.name = None
        return series_result
    else:
        return DataFrameGroupBy(
            self._df.T,
            self._by,
            0,
            drop=self._drop,
            idx_name=self._idx_name,
            **self._kwargs,
        ).size()