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/486#issuecomment-349582067,https://api.github.com/repos/pydata/xarray/issues/486,349582067,MDEyOklzc3VlQ29tbWVudDM0OTU4MjA2Nw==,167802,2017-12-06T09:24:16Z,2017-12-06T09:24:16Z,CONTRIBUTOR,"@shoyer absolutely, I will look into it, soon I hope","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612
https://github.com/pydata/xarray/issues/486#issuecomment-348910192,https://api.github.com/repos/pydata/xarray/issues/486,348910192,MDEyOklzc3VlQ29tbWVudDM0ODkxMDE5Mg==,167802,2017-12-04T09:43:02Z,2017-12-04T09:43:02Z,CONTRIBUTOR,"@jhamman One possibility would be to have a `.resample` on a DataArray (or equivalent independent function) that would be provided also a set of new coordinates, and that would return a new DataArray resampled to the new coordinates. One step further would be to implement this in `sel` or `isel` directly somehow.","{""total_count"": 3, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 3, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612
https://github.com/pydata/xarray/issues/486#issuecomment-348165798,https://api.github.com/repos/pydata/xarray/issues/486,348165798,MDEyOklzc3VlQ29tbWVudDM0ODE2NTc5OA==,167802,2017-11-30T11:47:06Z,2017-11-30T11:47:06Z,CONTRIBUTOR,thanks @shoyer ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612
https://github.com/pydata/xarray/issues/486#issuecomment-325999424,https://api.github.com/repos/pydata/xarray/issues/486,325999424,MDEyOklzc3VlQ29tbWVudDMyNTk5OTQyNA==,950575,2017-08-30T14:00:26Z,2017-08-30T14:00:26Z,CONTRIBUTOR,@JiaweiZhuang let's discuss that in the feedstock issue tracker to avoid cluttering xarray's.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612
https://github.com/pydata/xarray/issues/486#issuecomment-325973754,https://api.github.com/repos/pydata/xarray/issues/486,325973754,MDEyOklzc3VlQ29tbWVudDMyNTk3Mzc1NA==,950575,2017-08-30T12:22:13Z,2017-08-30T12:22:13Z,CONTRIBUTOR,">  then some effort needs to be made to build conda recipes and other infrastructure for distributing and building the platform.

Like https://github.com/conda-forge/esmf-feedstock :wink:

(Windows is still a problem b/c of the `Fortran` compiler.)","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612
https://github.com/pydata/xarray/issues/486#issuecomment-291953242,https://api.github.com/repos/pydata/xarray/issues/486,291953242,MDEyOklzc3VlQ29tbWVudDI5MTk1MzI0Mg==,3169620,2017-04-05T18:29:33Z,2017-04-05T18:29:53Z,CONTRIBUTOR,"@jhamman @godfrey4000 - I'm not sure of the status of this, but I'm the lead developer on a package called [CIS](https://github.com/cedadev/cis) which might be useful/relevant. 

It was designed as a command line tool to allow easy collocation (resampling) between different model and observation datasets, but is now also a Python library. We spent a fair amount of time thinking about the various permutations and you can see some of the details in our paper [here](http://www.geosci-model-dev.net/9/3093/2016/). Internally we currently use [Iris](https://github.com/scitools/iris) Cube-like objects but it would be pretty easy to operate on xarray Datasets since they share a similar design.

The basic syntax is: 
```
from CIS import read_data
X = read_data('some_obs_data.nc')
Y = read_data('some_other_data.nc')
X.sampled_from(Y)
# or...
Y.collocated_onto(X)
```
Happy to discuss further here, or in `xmap`.","{""total_count"": 5, ""+1"": 5, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612