DataArray groupby returning Dataset broken in some cases

[aulemahal]

What happened?

This is a the reverse problem of #6379, the DataArrayGroupBy._combine method seems broken when the mapped function returns a Dataset (which worked before #5692).

What did you expect to happen?

No response

Minimal Complete Verifiable Example

import xarray as xr

ds = xr.tutorial.open_dataset("air_temperature")

ds.air.resample(time="YS").map(lambda grp: grp.mean("time").to_dataset())

Relevant log output

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [3], in <module>
----> 1 ds.air.resample(time="YS").map(lambda grp: grp.mean("time").to_dataset())

File ~/Python/myxarray/xarray/core/resample.py:223, in DataArrayResample.map(self, func, shortcut, args, **kwargs)
    180 """Apply a function to each array in the group and concatenate them
    181 together into a new array.
    182 
   (...)
    219     The result of splitting, applying and combining this array.
    220 """
    221 # TODO: the argument order for Resample doesn't match that for its parent,
    222 # GroupBy
--> 223 combined = super().map(func, shortcut=shortcut, args=args, **kwargs)
    225 # If the aggregation function didn't drop the original resampling
    226 # dimension, then we need to do so before we can rename the proxy
    227 # dimension we used.
    228 if self._dim in combined.coords:

File ~/Python/myxarray/xarray/core/groupby.py:835, in DataArrayGroupByBase.map(self, func, shortcut, args, **kwargs)
    833 grouped = self._iter_grouped_shortcut() if shortcut else self._iter_grouped()
    834 applied = (maybe_wrap_array(arr, func(arr, *args, **kwargs)) for arr in grouped)
--> 835 return self._combine(applied, shortcut=shortcut)

File ~/Python/myxarray/xarray/core/groupby.py:869, in DataArrayGroupByBase._combine(self, applied, shortcut)
    867     index, index_vars = create_default_index_implicit(coord)
    868     indexes = {k: index for k in index_vars}
--> 869     combined = combined._overwrite_indexes(indexes, coords=index_vars)
    870 combined = self._maybe_restore_empty_groups(combined)
    871 combined = self._maybe_unstack(combined)

TypeError: _overwrite_indexes() got an unexpected keyword argument 'coords'

Anything else we need to know?

I guess the same solution as #6386 could be used!

Environment

INSTALLED VERSIONS

commit: None
python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:39:48)
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 5.16.13-arch1-1
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: fr_CA.utf8
LOCALE: ('fr_CA', 'UTF-8')
libhdf5: 1.12.0
libnetcdf: 4.7.4

xarray: 2022.3.1.dev16+g3ead17ea
pandas: 1.4.0
numpy: 1.20.3
scipy: 1.7.1
netCDF4: 1.5.7
pydap: None
h5netcdf: 0.11.0
h5py: 3.4.0
Nio: None
zarr: 2.10.0
cftime: 1.5.0
nc_time_axis: 1.3.1
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.08.0
distributed: 2021.08.0
matplotlib: 3.4.3
cartopy: None
seaborn: None
numbagg: None
fsspec: 2021.07.0
cupy: None
pint: 0.18
sparse: None
setuptools: 57.4.0
pip: 21.2.4
conda: None
pytest: 6.2.5
IPython: 8.0.1
sphinx: 4.1.2

[benbovy]

Ah yes, good catch @aulemahal. I'd be surprised if such example of returning a Dataset from DataArray groups is a common case, but since it seems to work well there no reason not to support it?

-> #6394