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/418#issuecomment-111943792,https://api.github.com/repos/pydata/xarray/issues/418,111943792,MDEyOklzc3VlQ29tbWVudDExMTk0Mzc5Mg==,10194086,2015-06-15T06:17:41Z,2015-06-15T06:17:41Z,MEMBER,"ok thank you for looking at it and the clarification.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,84068169
https://github.com/pydata/xarray/issues/418#issuecomment-108014220,https://api.github.com/repos/pydata/xarray/issues/418,108014220,MDEyOklzc3VlQ29tbWVudDEwODAxNDIyMA==,10194086,2015-06-02T16:57:52Z,2015-06-02T16:58:52Z,MEMBER,"I did a short hack - not sure if it is of any help...

#420

```
import numpy as np
import xray
temp = 15 + 8 * np.random.randn(20)
lat = np.arange(0, 20)
ds = xray.Dataset({'temperature': ('lat',  temp)}, coords={'lat' : lat})
ds.sel(lat=slice(1.2, 5.9)) # lat = 2 3 4 5
ds.sel(lat=slice(1.2, 5.9), method='nearest') # lat = 1 2 3 4 5 6
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,84068169