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/1989#issuecomment-373226888,https://api.github.com/repos/pydata/xarray/issues/1989,373226888,MDEyOklzc3VlQ29tbWVudDM3MzIyNjg4OA==,6815844,2018-03-15T01:10:37Z,2018-03-15T01:15:33Z,MEMBER,"I notice that bottleneck does the dtype conversion.
I think in your environment bottleneck is installed.

```python
In [9]: np.sum(a)  # equivalent to a.sum(), using bottleneck
Out[9]: 
<xarray.DataArray ()>
array(499943.21875)

In [10]: np.sum(a.data)  # numpy native
Out[10]: 499941.53

In [15]: bn.nansum(a.data)
Out[15]: 499943.21875

In [11]: a.sum(dim=('x', 'y'))  # multiple dims calls native np.sum
Out[11]: 
<xarray.DataArray ()>
array(499941.53, dtype=float32)
```

It might be an upstream issue.
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