html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/4995#issuecomment-1110101560,https://api.github.com/repos/pydata/xarray/issues/4995,1110101560,IC_kwDOAMm_X85CKs44,8699967,2022-04-26T18:09:18Z,2022-04-26T18:12:14Z,CONTRIBUTOR,"Example using `nearest` & `tolerance` with  `reindex` & `sel` when dims don't match based on the example in `sel`:

```python
import numpy
import xarray

da = xarray.DataArray(
    numpy.arange(25).reshape(5, 5),
    coords={""x"": numpy.arange(5), ""y"": numpy.arange(5)},
    dims=(""x"", ""y""),
)
tgt_x = numpy.linspace(0, 4, num=5) + 0.5
tgt_y = numpy.linspace(0, 4, num=5) + 0.5
da = da.reindex(
    x=tgt_x, y=tgt_y, method=""nearest"", tolerance=0.2, fill_value=numpy.nan
).sel(
    x=xarray.DataArray(tgt_x, dims=""points""),
    y=xarray.DataArray(tgt_y, dims=""points""),
)
```
Output:
```
<xarray.DataArray (points: 5)>
array([nan, nan, nan, nan, nan])
Coordinates:
    x        (points) float64 0.5 1.5 2.5 3.5 4.5
    y        (points) float64 0.5 1.5 2.5 3.5 4.5
Dimensions without coordinates: points
```
Side note: I don't think it makes sense to add `fill_value` to `sel` as it would require adding new coordinates that didn't exist previously. Calling `reindex` first makes that more clear in my opinion.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,822320976