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
1192449540,I_kwDOAMm_X85HE1YE,6439,Unstacking the diagonals of a sequence of matrices raises ValueError: IndexVariable objects must be 1-dimensional,22566757,closed,0,,,5,2022-04-05T00:09:55Z,2022-05-02T19:05:19Z,2022-05-02T19:00:47Z,CONTRIBUTOR,,,,"### What happened?

In my work, I produced a sequence of covariance matrices for a 2-D quantity.  I wanted to extract the diagonal of the covariance matrices, then make that diagonal 2-D so I could plot it.

I could unstack the 2-D dimensions in the sequence of covariance matrices without issue.  I figured out how to extract the diagonal of the covariance matrices.  Unstacking the diagonal using the same procedure raised a `ValueError`.

### What did you expect to happen?

I expected the sequence of one-dimensional diagonals to unstack into a sequence of two-dimensional fields so I could plot them with pcolormesh.

I can make this happen by unstacking the two dimensions (producing a 5-D DataArray) and extracting the diagonals from that, but I don't see a reason it shouldn't work in the other order.

### Minimal Complete Verifiable Example

```Python
import numpy as np
import xarray

# Working:
test = xarray.DataArray(
    np.eye(12),
    dims=(""dim0"", ""adj_dim0""),
    coords={
        ""dim0_0"": ((""dim0"",), np.repeat(np.arange(3), 4)),
        ""dim0_1"": ((""dim0"",), np.tile(np.arange(4), 3)),
    },
)
unstacked = test.set_index(dim0=[""dim0_0"", ""dim0_1""]).unstack(""dim0"")
diag_index = xarray.DataArray(np.arange(test.shape[0]), dims=(""diag"",))
unstacked_diag = (
    test.isel(dim0=diag_index, adj_dim0=diag_index)
    .set_index(diag=[""dim0_0"", ""dim0_1""])
    .unstack(""diag"")
)

# Not working:
test = xarray.DataArray(
    dims=(""dim1"", ""dim0"", ""adj_dim0""),
    data=np.tile(np.eye(12), (2, 1, 1)),
    coords={
        ""dim0"": np.arange(12),
        ""dim0_0"": ((""dim0"",), np.repeat(np.arange(3), 4)),
        ""dim0_1"": ((""dim0"",), np.tile(np.arange(4), 3)),
        ""adj_dim0"": np.arange(12),
        ""adj_dim0_0"": ((""adj_dim0"",), np.repeat(np.arange(3), 4)),
        ""adj_dim0_1"": ((""adj_dim0"",), np.tile(np.arange(4), 3)),
    },
)
unstacked = test.set_index(
    dim0=[""dim0_0"", ""dim0_1""], adj_dim0=[""adj_dim0_0"", ""adj_dim0_1""]
).unstack([""dim0"", ""adj_dim0""])

diag_index0 = xarray.DataArray(np.arange(unstacked.shape[1]), dims=(""diag_0"",))
diag_index1 = xarray.DataArray(np.arange(unstacked.shape[2]), dims=(""diag_1"",))
unstacked_diag = unstacked.isel(
    dim0_0=diag_index0,
    dim0_1=diag_index1,
    adj_dim0_0=diag_index0,
    adj_dim0_1=diag_index1,
)

diag_index = xarray.DataArray(np.arange(test.shape[1]), dims=(""diag"",))
test.isel(dim0=diag_index, adj_dim0=diag_index).set_index(
    diag=[""dim0_0"", ""dim0_1""]
).unstack(""diag"")
```


### Relevant log output

```Python
Traceback (most recent call last):
  File ""./test.py"", line 50, in <module>
    ).unstack(""diag"")
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/dataarray.py"", line 2201, in unstack
    ds = self._to_temp_dataset().unstack(dim, fill_value, sparse)
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/dataset.py"", line 4214, in unstack
    result = result._unstack_once(dim, fill_value, sparse)
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/dataset.py"", line 4070, in _unstack_once
    variables[name] = var._unstack_once(
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/variable.py"", line 1690, in _unstack_once
    return self._replace(dims=new_dims, data=data)
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/variable.py"", line 978, in _replace
    return type(self)(dims, data, attrs, encoding, fastpath=True)
  File ""~/.conda/envs/plotting/lib/python3.10/site-packages/xarray/core/variable.py"", line 2668, in __init__
    raise ValueError(f""{type(self).__name__} objects must be 1-dimensional"")
ValueError: IndexVariable objects must be 1-dimensional
```


### Anything else we need to know?

_No response_

### Environment

INSTALLED VERSIONS
------------------
commit: None
python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:39:04) [GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.59.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.8.1

xarray: 2022.3.0
pandas: 1.4.2
numpy: 1.22.3
scipy: 1.8.0
netCDF4: 1.5.8
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.0
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.5.1
cartopy: 0.20.2
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
setuptools: 61.3.1
pip: 22.0.4
conda: None
pytest: None
IPython: None
sphinx: None
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