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
1128821318,PR_kwDOAMm_X84yULfs,6260,allow coordinates to be independent of `region` selection in to_zarr,43613877,open,0,,,2,2022-02-09T17:21:19Z,2023-10-24T23:37:21Z,,CONTRIBUTOR,,1,pydata/xarray/pulls/6260,"The ``region`` argument has been validated too strictly as coordinates needed to have a common dimension with the selected dimensions in ``region``. The validation is now restricted to data variables.

<!-- Feel free to remove check-list items aren't relevant to your change -->

- [X] Closes #6069 
- [X] Tests added
- [X] User visible changes (including notable bug fixes) are documented in `whats-new.rst`
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822320976,MDU6SXNzdWU4MjIzMjA5NzY=,4995,"KeyError when selecting ""nearest"" data with given tolerance ",43613877,open,0,,,8,2021-03-04T17:00:13Z,2022-10-25T14:35:35Z,,CONTRIBUTOR,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**: Selecting data with `ds.sel(index=given_index, method=""nearest"", tolerance=tolerance)` only works in case for each `given_index` exists an `index` that is within the given `tolerance`, otherwise a `KeyError: ""not all values found in index 'index'"" occurs.

**What you expected to happen**: I would expect, that those indices that are not within the `tolerance` would simply be dropped.

**Minimal Complete Verifiable Example**:

```python
import xarray as xr
ds = xr.DataArray([1,2,3,4,5], dims=[""lat""], coords={'lat':[10,20,30,50,60]})

# working example, all latitudes are within the tolerance
ds.sel(lat=[5,15,40], method=""nearest"", tolerance=10)
#<xarray.DataArray (lat: 3)>
#array([1, 2, 4])
#Coordinates:
#  * lat      (lat) int64 10 20 50

# failing example, latitude 40 is not within the tolerance
ds.sel(lat=[5,15,40], method=""nearest"", tolerance=5)
# KeyError: ""not all values found in index 'lat'""
```

I would expect
```
>>> ds.sel(lat=[5,15,40], method=""nearest"", tolerance=5)
<xarray.DataArray (lat: 2)>
array([1, 2])
Coordinates:
  * lat      (lat) int64 10 20
```

**Anything else we need to know?**:

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

<!-- Paste the output here xr.show_versions() here -->
INSTALLED VERSIONS
------------------
commit: 66acafa7f1f1477cfd6c5b7c3458859763433092
python: 3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:12:38) 
[Clang 11.0.1 ]
python-bits: 64
OS: Darwin
OS-release: 20.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.15.2.dev452+g66acafa7.d20210304
pandas: 1.2.3
numpy: 1.20.1
scipy: 1.6.0
netCDF4: 1.5.6
pydap: installed
h5netcdf: 0.10.0
h5py: 3.1.0
Nio: None
zarr: 2.6.1
cftime: 1.4.1
nc_time_axis: 1.2.0
PseudoNetCDF: installed
rasterio: 1.2.0
cfgrib: 0.9.8.5
iris: 2.4.0
bottleneck: 1.3.2
dask: 2021.02.0
distributed: 2021.02.0
matplotlib: 3.3.4
cartopy: 0.18.0
seaborn: 0.11.1
numbagg: installed
pint: 0.16.1
setuptools: 49.6.0.post20210108
pip: 20.2.4
conda: None
pytest: 6.2.2
IPython: None
sphinx: None

</details>
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1362683132,I_kwDOAMm_X85ROOT8,6995,`mean` returns empty DataArray for `groupby_bins` containing `datetime64`,43613877,open,0,,,1,2022-09-06T04:20:40Z,2022-09-30T17:18:22Z,,CONTRIBUTOR,,,,"### What happened?

Applying the `mean` operator to an xarray dataset that has been grouped by bins, removes variables containing values of type `datetime64`.

### What did you expect to happen?

I expect that all variables are preserved after applying the `mean`-operator. For `min` and `max` this works as expected. `sum` is not meaningful, so it makes sense that the variable is dropped in that case as well.

### Minimal Complete Verifiable Example

```Python
import numpy as np
import pandas as pd
import xarray as xr

times = pd.date_range('2020-01-01', '2020-02-01', freq='1H')
index = np.arange(len(times))
bins = np.arange(0,len(index),5)
ds=xr.Dataset({'time':('index', times),'float':('index', np.linspace(0,1,len(index)))},coords={'index':index})

ds.groupby_bins('index', bins).mean()
<xarray.Dataset>
Dimensions:     (index_bins: 148)
Coordinates:
  * index_bins  (index_bins) object (0, 5] (5, 10] ... (730, 735] (735, 740]
Data variables:
    float       (index_bins) float64 0.004032 0.01075 0.01747 ... 0.9852 0.9919

ds.groupby_bins('index', bins).min()
<xarray.Dataset>
Dimensions:     (index_bins: 148)
Coordinates:
  * index_bins  (index_bins) object (0, 5] (5, 10] ... (730, 735] (735, 740]
Data variables:
    time        (index_bins) datetime64[ns] 2020-01-01T01:00:00 ... 2020-01-3...
    float       (index_bins) float64 0.001344 0.008065 0.01478 ... 0.9825 0.9892
```


### MVCE confirmation

- [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:43:44) [Clang 13.0.1 ]
python-bits: 64
OS: Darwin
OS-release: 21.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2022.6.0
pandas: 1.4.4
numpy: 1.23.2
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.5.3
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.8.2
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.3.0
pip: 22.2.2
conda: None
pytest: None
IPython: 8.4.0
sphinx: None



</details>
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