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/1651#issuecomment-364503678,https://api.github.com/repos/pydata/xarray/issues/1651,364503678,MDEyOklzc3VlQ29tbWVudDM2NDUwMzY3OA==,5635139,2018-02-09T17:36:29Z,2018-02-09T17:36:29Z,MEMBER,Closed by https://github.com/pydata/xarray/pull/1640,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338882778,https://api.github.com/repos/pydata/xarray/issues/1651,338882778,MDEyOklzc3VlQ29tbWVudDMzODg4Mjc3OA==,2443309,2017-10-24T05:59:44Z,2017-10-24T05:59:44Z,MEMBER,"@MaximilianR - I'm a big +1 on these features. Pandas has a `missing` module. I think these methods, combined with the interpolation methods I'm working on in #1640 would cover a large chunk of our use cases.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338868401,https://api.github.com/repos/pydata/xarray/issues/1651,338868401,MDEyOklzc3VlQ29tbWVudDMzODg2ODQwMQ==,5635139,2017-10-24T04:15:47Z,2017-10-24T04:15:47Z,MEMBER,"Ah, that explains a lot. Thanks for the clarification. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338860711,https://api.github.com/repos/pydata/xarray/issues/1651,338860711,MDEyOklzc3VlQ29tbWVudDMzODg2MDcxMQ==,1217238,2017-10-24T03:18:37Z,2017-10-24T03:18:37Z,MEMBER,"Other numpy functions, e.g., `flip` check for some attributes and then assume duck type compatibility if found. For example, `flip` is turned into an indexing call.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338860305,https://api.github.com/repos/pydata/xarray/issues/1651,338860305,MDEyOklzc3VlQ29tbWVudDMzODg2MDMwNQ==,1217238,2017-10-24T03:16:00Z,2017-10-24T03:16:00Z,MEMBER,"> Right, but numpy functions return the original type?

Not quite -- many numpy functions check for a method of the same name on their argument and call it instead of the numpy routine. If you look at the source of `np.sum`, it first checks for a `sum` method on its argument and calls that method instead if found. Otherwise, it coerces the argument to a numpy array and calls the numpy method.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338855039,https://api.github.com/repos/pydata/xarray/issues/1651,338855039,MDEyOklzc3VlQ29tbWVudDMzODg1NTAzOQ==,5635139,2017-10-24T02:40:35Z,2017-10-24T02:40:35Z,MEMBER,"Right, but numpy functions return the original type?

```
In [6]: da=xr.DataArray(np.random.rand(2,4))

In [12]: np.sum(da, axis=1)
Out[12]:
<xarray.DataArray (dim_0: 2)>
array([ 0.880766,  2.058156])
Dimensions without coordinates: dim_0


In [14]: np.flip(da, 1)
Out[14]:
<xarray.DataArray (dim_0: 2, dim_1: 4)>
array([[ 0.279932,  0.307569,  0.291855,  0.001411],
       [ 0.681486,  0.556972,  0.083212,  0.736487]])
Dimensions without coordinates: dim_0, dim_1
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297
https://github.com/pydata/xarray/issues/1651#issuecomment-338822929,https://api.github.com/repos/pydata/xarray/issues/1651,338822929,MDEyOklzc3VlQ29tbWVudDMzODgyMjkyOQ==,1217238,2017-10-23T23:11:03Z,2017-10-23T23:11:03Z,MEMBER,"> One small issue, I wonder if anyone has come across this: bottleneck returns the numpy array rather than the DataArray - is that because it's not operating with the correct numpy interface?

Can you explain? I don't think bottleneck is xarray aware, so I'm not surprised by this. NumPy doesn't have a generic interface for external functions (only [ufuncs](https://docs.scipy.org/doc/numpy-1.13.0/reference/ufuncs.html)).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,267826297