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/60#issuecomment-276540506,https://api.github.com/repos/pydata/xarray/issues/60,276540506,MDEyOklzc3VlQ29tbWVudDI3NjU0MDUwNg==,8982598,2017-02-01T00:43:52Z,2017-02-01T00:43:52Z,CONTRIBUTOR,"Would using `obj.fillna(0)` not mess with `argmax` if for instance all the data is negative? Could fill with the min value instead?

Ah yes true. I was slightly anticipating e.g. filling with NaT if the `dim` was time-like, though time types are not something I am familiar with.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,29136905
https://github.com/pydata/xarray/issues/60#issuecomment-276537615,https://api.github.com/repos/pydata/xarray/issues/60,276537615,MDEyOklzc3VlQ29tbWVudDI3NjUzNzYxNQ==,8982598,2017-02-01T00:26:24Z,2017-02-01T00:26:24Z,CONTRIBUTOR,"Ah yes both ways are working now, thanks. Just had a little play around with timings, and this seems like a reasonably quick way to achieve correct NaN behaviour:

```python
def xr_idxmax(obj, dim):
    sig = ([(dim,), (dim,)], [()])
    kwargs = {'axis': -1}
    
    allna = obj.isnull().all(dim)
    
    return apply_ufunc(gufunc_idxmax, obj.fillna(-np.inf), obj[dim],
                       signature=sig, kwargs=kwargs,
                       dask_array='allowed').where(~allna).fillna(np.nan)
```

i.e. originally replace all NaN values with -Inf, use the usual `argmax`, and remask the all-NaN values afterwards.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,29136905
https://github.com/pydata/xarray/issues/60#issuecomment-276232678,https://api.github.com/repos/pydata/xarray/issues/60,276232678,MDEyOklzc3VlQ29tbWVudDI3NjIzMjY3OA==,8982598,2017-01-31T00:06:02Z,2017-01-31T00:06:02Z,CONTRIBUTOR,"So I thought `take` was just the functional equivalent of fancy indexing - I spotted it in the dask api and assumed it would work but having tried it does indeed just raise a 'not implemented error'. Just as a note, with the `map_blocks` approach above `take` is working for some cases where `x[inds, ]` is not -- related to #1237?

Regarding edge cases: multiple maxes is presumably fine as long as user is aware it just takes the first.
However, `nanargmax` is probably the actual desired function here, but looks like it will raise on all-nan slices. Would dropping these and then re-aligning be too much overhead?

","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,29136905
https://github.com/pydata/xarray/issues/60#issuecomment-275778443,https://api.github.com/repos/pydata/xarray/issues/60,275778443,MDEyOklzc3VlQ29tbWVudDI3NTc3ODQ0Mw==,8982598,2017-01-27T21:24:31Z,2017-01-27T21:24:31Z,CONTRIBUTOR,"Just as I am interested in having this functionality, and the new `apply_ufunc` is available, would something along these lines suffice?

```python
from wherever import argmax, take  # numpy or dask

def gufunc_idxmax(x, y, axis=None):
    indx = argmax(x, axis)
    return take(y, indx)

def idxmax(obj, dim):
    sig = ([(dim,), (dim,)], [()])
    kwargs = {'axis': -1}
    return apply_ufunc(gufunc_idxmin, obj, obj[dim],
                       signature=sig, kwargs=kwargs,
                       dask_array='allowed')
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,29136905