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-521413970,https://api.github.com/repos/pydata/xarray/issues/3218,521413970,MDEyOklzc3VlQ29tbWVudDUyMTQxMzk3MA==,923438,2019-08-14T20:52:06Z,2019-08-14T20:52:06Z,NONE,"That looks correct. Let me try and revert back to you

On Wed, Aug 14, 2019, 16:44 Maximilian Roos <notifications@github.com>
wrote:

> 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
> <https://github.com/fjanoos> ?)
>
> @fjanoos <https://github.com/fjanoos> can you confirm this is what you're
> looking for?
>
> 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
>
> —
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","{""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-521404974,https://api.github.com/repos/pydata/xarray/issues/3218,521404974,MDEyOklzc3VlQ29tbWVudDUyMTQwNDk3NA==,923438,2019-08-14T20:25:52Z,2019-08-14T20:25:52Z,NONE,"As of now, a simple workaround would be to do these tasks in pandas and
switch back and forth.

A couple of years ago - before pandas had pd.merge_asof - I had implemented
a version of this logic in numba when working with numpy arrays.
It was blazingly fast - and if there is interest I can try to dig it up ? I
would need some help  making it work for xarrays and publishing it into the
master branch.



On Wed, Aug 14, 2019, 14:12 Maximilian Roos <notifications@github.com>
wrote:

> 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.
>
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","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480786385