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
1388326248,I_kwDOAMm_X85SwC1o,7093,xarray allows several types for netcdf attributes. Is it expected ?,10563614,open,0,,,3,2022-09-27T20:20:46Z,2022-10-04T20:46:32Z,,CONTRIBUTOR,,,,"### What is your issue?

Xarray is permissive regarding the type of the attributes. If using a wrong type, the error reveals the valid types: For serialization to netCDF files, its value must be of one of the following types: str, Number, ndarray, number, list, tuple

Using a non iterable type used to raise an Exception when reading the saved netcdf, but this is now solved with #7085

The pending question is whether it is valid to save netcdf attributes with type other than a string or not.
The following lines are working (in a notebook):

```python
xr.DataArray([1, 2, 3], attrs={'units': 1}, name='x').to_netcdf(""tmp.nc"")
!ncdump tmp.nc

xr.DataArray([1, 2, 3], attrs={'units': np.nan}, name='x').to_netcdf(""tmp.nc"")
!ncdump tmp.nc

xr.DataArray([1, 2, 3], attrs={'units': ['xarray', 'is', 'very', 'permissive', ]}, name='x').to_netcdf(""tmp.nc"")
!ncdump tmp.nc
```
On the other hand, the following line raises an error:

```python
xr.DataArray([1, 2, 3], attrs={'units': None}, name='x').to_netcdf(""tmp.nc"")

```

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709503596,MDU6SXNzdWU3MDk1MDM1OTY=,4465,combine_by_coords could use allclose instead of equal to compare coordinates,10563614,open,0,,,4,2020-09-26T09:26:05Z,2020-09-26T21:30:35Z,,CONTRIBUTOR,,,,"<!-- Please do a quick search of existing issues to make sure that this has not been asked before. -->

**Is your feature request related to a problem? Please describe.**

When a coordinate in different dataset / netcdf files has slightly different values, combine_by_coords considers the coordinate are different and attempts a concatenation of the coordinates.

Concretely, I produce netcdf with (lat, lon, time) coordinates, annually. Apparently the lat is not the same in all the files (difference is 1e-14), which I suspect is due to different pyproj version used to produce the lon,lat grid. Reprocessing all the annual netcdf is not an option. When using open_mfdataset on these netcdf, the lat coordinate is concatenated which leads to a MemoryError in my case.

**Describe the solution you'd like**
Two options:
- add a coord_tolerance argument to xr.combine_by_coords and use np.allclose to compare the coordinates. In line 69 combine.py the comparison uses strict equality ""if not all(index.equals(indexes[0]) for index in indexes[1:]):"". This does not break the compatibility because coord_tolerance=0 should be the default.

- add an argument to explicity list the coordinates to NOT concatenate. I tried to play with the coords argument to solve my problem, but was not succesfull.

**Describe alternatives you've considered**

- I certainly could find a workaround for this specific case, but I often had issue with the magic in combine_by_coords, and imho adding more control by the user would be useful in general.

**Additional context**

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