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/pull/1272#issuecomment-331283075,https://api.github.com/repos/pydata/xarray/issues/1272,331283075,MDEyOklzc3VlQ29tbWVudDMzMTI4MzA3NQ==,1217238,2017-09-21T21:11:07Z,2017-09-21T21:11:07Z,MEMBER,"We just bumped numpy to 1.11, but 1.12 would be too new.

Let's just add a `np.flip` backport to `core/npcompat.py`. The [whole function](https://github.com/numpy/numpy/blob/master/numpy/lib/function_base.py#L140-L209) is only a couple of lines.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,208215185
https://github.com/pydata/xarray/pull/1272#issuecomment-324175792,https://api.github.com/repos/pydata/xarray/issues/1272,324175792,MDEyOklzc3VlQ29tbWVudDMyNDE3NTc5Mg==,1217238,2017-08-22T23:05:49Z,2017-08-22T23:05:49Z,MEMBER,"> I've opted not to include a chart outlining the various upsampling options...

This is OK by me","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,208215185
https://github.com/pydata/xarray/pull/1272#issuecomment-323500774,https://api.github.com/repos/pydata/xarray/issues/1272,323500774,MDEyOklzc3VlQ29tbWVudDMyMzUwMDc3NA==,1217238,2017-08-19T04:58:56Z,2017-08-19T04:58:56Z,MEMBER,I like your approach here! Just some various comments on the implementation.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,208215185
https://github.com/pydata/xarray/pull/1272#issuecomment-283473505,https://api.github.com/repos/pydata/xarray/issues/1272,283473505,MDEyOklzc3VlQ29tbWVudDI4MzQ3MzUwNQ==,1217238,2017-03-01T21:19:13Z,2017-03-01T21:19:13Z,MEMBER,"> I can't really find many examples of people using this as a substitute for time group-bys... it seems that's what the pd.TimeGrouper is for, in conjunction with a normal .groupby().

I think this is mostly because TimeGrouper has been around far longer than non-aggregating resample.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,208215185
https://github.com/pydata/xarray/pull/1272#issuecomment-281189948,https://api.github.com/repos/pydata/xarray/issues/1272,281189948,MDEyOklzc3VlQ29tbWVudDI4MTE4OTk0OA==,1217238,2017-02-20T21:50:05Z,2017-02-20T21:50:05Z,MEMBER,"> The only issue now is the signature for init() in Data{set,Array}Resample, where we have to add in two keyword arguments. Python 2.x doesn't like named arguments after *args. There are a few options here, mostly just playing with **kwargs as in this StackOverflow thread.

Yes, use `pop`, e.g., `dim = kwargs.pop('dim', None)`. `pop` removes the arguments from kwargs, so you can pass on the remaining ones unchanged to the super class method.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,208215185