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/328#issuecomment-75475798,https://api.github.com/repos/pydata/xarray/issues/328,75475798,MDEyOklzc3VlQ29tbWVudDc1NDc1Nzk4,306380,2015-02-23T00:42:39Z,2015-02-23T00:42:39Z,MEMBER,"Am I right in thinking that this is almost equivalent to fancy indexing with a list of indices?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,58310637
https://github.com/pydata/xarray/issues/328#issuecomment-75417769,https://api.github.com/repos/pydata/xarray/issues/328,75417769,MDEyOklzc3VlQ29tbWVudDc1NDE3NzY5,306380,2015-02-22T03:37:22Z,2015-02-22T03:37:22Z,MEMBER,"> support super-imposing array values inter-leaved on top of a constant array of NaN (necessary for many alignment operations)

@shoyer can you clarify this one?  Would the `np.choose` interface satisfy this?

``` Python
In [1]: import numpy as np

In [2]: a = np.arange(4).reshape(2, 2)

In [3]: a
Out[3]: 
array([[0, 1],
       [2, 3]])

In [4]: x = np.array([[True, False], [True, True]])

In [5]: np.choose(x, [-10, a])
Out[5]: 
array([[  0, -10],
       [  2,   3]])
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,58310637
https://github.com/pydata/xarray/issues/328#issuecomment-75276367,https://api.github.com/repos/pydata/xarray/issues/328,75276367,MDEyOklzc3VlQ29tbWVudDc1Mjc2MzY3,306380,2015-02-20T17:06:41Z,2015-02-20T17:06:41Z,MEMBER,"- support for NaN skipping aggregations
  
  Presumably we could drop in `numbagg` here.  The reductions are generally pretty straightforward to extend.  I can do this relatively soon.  See https://github.com/ContinuumIO/dask/blob/master/dask/array/reductions.py#L43-L111
- support for interleaved concatenation (necessary for transformations by group, which are quite common)
  
  Do we have this already?  Or rather can you point me to how you would do this with NumPy.
- support super-imposing array values inter-leaved on top of a constant array of NaN (necessary for many alignment operations)
  
  Would this be solved by an elementwise `ifelse` operation?  `ifelse(condition, x, y)`
- support ""orthogonal"" MATLAB-like array-based indexing along multiple dimensions
  
  You can do this now by repeated slicing `x[[1, 2, 3], :][:, [4, 5, 6]]` and get a fully efficient solution.  I can roll this in to the normal syntax though.  I might pause for a bit as I think about the break that this causes with NumPy but I'll probably go ahead anyway.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,58310637