issue_comments

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 addfill_valuetoselas it would require adding new coordinates that didn't exist previously. Callingreindex` first makes that more clear in my opinion.

Thanks @dcherian, this is doing the job. I'll close this issue as there seems to be no need to implement this into the sel method.

Introducing a fill_value seems like a good idea, such that the size of the output does not change compared to the intended selection. Choosing the original/requested coordinate as a label for the missing datapoint seems to be a valid choice because this position has been checked for valid data nearby without success. I would suggest, that the fill_value should then be automatically determined from the _FillValue, the datatype and only at last requires the fill_value to be set.

However, the shortcoming that I see in using a fill_value is that the indexing has to modify the data ( insert e.g. -999) and also 'invent' a new coordinate point ( here 40). This gets reasonably complex, when applying to a dataset with DataArrays of different types, e.g. ```python import numpy as np import xarray as xr

ds = xr.Dataset() ds['data1'] = xr.DataArray(np.array([1,2,3,4,5], dtype=int), dims=["lat"], coords={'lat':[10,20,30,50,60]}) ds['data2'] = xr.DataArray(np.array([1,2,3,4,5], dtype=float), dims=["lat"], coords={'lat':[10,20,30,50,60]}) `` Onefill_valuemight not fit to all data arrays being it because of the datatype or the actual data. E.g.-999might be a goodfill_value` for one DataArray but a valid datapoint in another one.