id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1831975171,I_kwDOAMm_X85tMbkD,8039,Update assign_coords with a MultiIndex to match new Coordinates API,20629530,closed,0,,,11,2023-08-01T20:22:41Z,2023-08-29T14:23:30Z,2023-08-29T14:23:30Z,CONTRIBUTOR,,,,"### What is your issue?

A pattern we used in `xclim` (and elsewhere) seems to be broken on the master.

See MWE:
```python3
import pandas as pd
import xarray as xr

da = xr.DataArray([1] * 730, coords={""time"": xr.date_range('1900-01-01', periods=730, freq='D', calendar='noleap')})
mulind = pd.MultiIndex.from_arrays((da.time.dt.year.values, da.time.dt.dayofyear.values), names=('year', 'doy'))

# Override previous time axis with new MultiIndex
da.assign_coords(time=mulind).unstack('time')
```

Now this works ok with both the current master and the latest release. However, if we chunk `da`, the last line now fails:
```python
da.chunk(time=50).assign_coords(time=mulind).unstack('time')
```
On the master, this gives: `ValueError: unmatched keys found in indexes and variables: {'year', 'doy'}`

Full traceback:

<details>
 
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[44], line 1
----> 1 da.chunk(time=50).assign_coords(time=mulind).unstack(""time"")

File ~/Projets/xarray/xarray/core/dataarray.py:2868, in DataArray.unstack(self, dim, fill_value, sparse)
   2808 def unstack(
   2809     self,
   2810     dim: Dims = None,
   2811     fill_value: Any = dtypes.NA,
   2812     sparse: bool = False,
   2813 ) -> DataArray:
   2814     """"""
   2815     Unstack existing dimensions corresponding to MultiIndexes into
   2816     multiple new dimensions.
   (...)
   2866     DataArray.stack
   2867     """"""
-> 2868     ds = self._to_temp_dataset().unstack(dim, fill_value, sparse)
   2869     return self._from_temp_dataset(ds)

File ~/Projets/xarray/xarray/core/dataset.py:5481, in Dataset.unstack(self, dim, fill_value, sparse)
   5479 for d in dims:
   5480     if needs_full_reindex:
-> 5481         result = result._unstack_full_reindex(
   5482             d, stacked_indexes[d], fill_value, sparse
   5483         )
   5484     else:
   5485         result = result._unstack_once(d, stacked_indexes[d], fill_value, sparse)

File ~/Projets/xarray/xarray/core/dataset.py:5365, in Dataset._unstack_full_reindex(self, dim, index_and_vars, fill_value, sparse)
   5362 else:
   5363     # TODO: we may depreciate implicit re-indexing with a pandas.MultiIndex
   5364     xr_full_idx = PandasMultiIndex(full_idx, dim)
-> 5365     indexers = Indexes(
   5366         {k: xr_full_idx for k in index_vars},
   5367         xr_full_idx.create_variables(index_vars),
   5368     )
   5369     obj = self._reindex(
   5370         indexers, copy=False, fill_value=fill_value, sparse=sparse
   5371     )
   5373 for name, var in obj.variables.items():

File ~/Projets/xarray/xarray/core/indexes.py:1435, in Indexes.__init__(self, indexes, variables, index_type)
   1433 unmatched_keys = set(indexes) ^ set(variables)
   1434 if unmatched_keys:
-> 1435     raise ValueError(
   1436         f""unmatched keys found in indexes and variables: {unmatched_keys}""
   1437     )
   1439 if any(not isinstance(idx, index_type) for idx in indexes.values()):
   1440     index_type_str = f""{index_type.__module__}.{index_type.__name__}""

ValueError: unmatched keys found in indexes and variables: {'year', 'doy'}

</details>

This seems related to PR #7368.

The reason for the title of this issue is that in both versions, I now realize the `da.assign_coords(time=mulind)` prints as:
```
<xarray.DataArray (time: 730)>
dask.array<xarray-<this-array>, shape=(730,), dtype=int64, chunksize=(50,), chunktype=numpy.ndarray>
Coordinates:
  * time     (time) object MultiIndex
```
Something's fishy, because the two ""sub"" indexes are not showing.

And indeed, with the current master, I can get this to work by doing (again changing the last line):
```python
da2 = xr.DataArray(da.data, coords=xr.Coordinates.from_pandas_multiindex(mulind, 'time'))
da2.chunk(time=50).unstack('time')
```
But it seems a bit odd to me that we need to reconstruct the DataArray to replace its coordinate with a ""MultiIndex"" one.

Thus, my questions are:

1. How does one properly _override_ a coordinate by a MultiIndex ? Is there a way to use `assign_coords` ? If not, then this issue would become a feature request.
2. Is this a regression ? Or was I just ""lucky"" before ?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8039/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue