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/3218#issuecomment-521411228,https://api.github.com/repos/pydata/xarray/issues/3218,521411228,MDEyOklzc3VlQ29tbWVudDUyMTQxMTIyOA==,5635139,2019-08-14T20:43:57Z,2019-08-14T20:43:57Z,MEMBER,"> How is merge_asof different from using reindex with method='pad'?

Yes this is right! Mea culpa. We can already use the pandas reindexing for the 1D case (which should cover your case @fjanoos ?)

@fjanoos can you confirm this is what you're looking for?

```python


In [4]: da=xr.DataArray(list('abcdefghil'), dims=['x'],coords=dict(x=range(10)))

In [8]: da.reindex(x=[0,2.5,2.6,2.7,5,6.2], method='nearest')
Out[8]:
<xarray.DataArray (x: 6)>
array(['a', 'd', 'd', 'd', 'f', 'g'], dtype='<U1')
Coordinates:
  * x        (x) float64 0.0 2.5 2.6 2.7 5.0 6.2

```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480786385
https://github.com/pydata/xarray/issues/3218#issuecomment-521357519,https://api.github.com/repos/pydata/xarray/issues/3218,521357519,MDEyOklzc3VlQ29tbWVudDUyMTM1NzUxOQ==,5635139,2019-08-14T18:12:43Z,2019-08-14T18:12:43Z,MEMBER,"I think this would be good. It would need to be implemented outside of python (cython / numba / etc) given the performance requirements. I'm not sure whether we could borrow the pandas functionality and apply it to multi-dimensional arrays.

Assuming we'd need to write our own, xarray doesn't have any cython dependencies, so I think it would be best in a separate and optional package. These could go in numbagg. 
It's non-trivial work, so someone would have to have a strong need for it.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480786385