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-585535983,https://api.github.com/repos/pydata/xarray/issues/1989,585535983,MDEyOklzc3VlQ29tbWVudDU4NTUzNTk4Mw==,26384082,2020-02-13T03:46:00Z,2020-02-13T03:46:00Z,NONE,"In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity

If this issue remains relevant, please comment here or remove the `stale` label; otherwise it will be marked as closed automatically
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,305373563
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.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,305373563
https://github.com/pydata/xarray/issues/1989#issuecomment-373221321,https://api.github.com/repos/pydata/xarray/issues/1989,373221321,MDEyOklzc3VlQ29tbWVudDM3MzIyMTMyMQ==,1828519,2018-03-15T00:37:26Z,2018-03-15T00:38:04Z,CONTRIBUTOR,@shoyer In my examples `rows = cols = 1000` (xarray 0.10.1).,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,305373563
https://github.com/pydata/xarray/issues/1989#issuecomment-373221066,https://api.github.com/repos/pydata/xarray/issues/1989,373221066,MDEyOklzc3VlQ29tbWVudDM3MzIyMTA2Ng==,1217238,2018-03-15T00:36:02Z,2018-03-15T00:36:02Z,MEMBER,"> Strangely, it says: AttributeError: module 'xarray' has no attribute 'show_versions' Perhaps I am on a very old version?

Yes, you're using a version of xarray prior to 0.10.

What value are you using for `rows`/`cols` in your example?

Note that due to a quirk of NumPy, `np.sum(a)` actually corresponds to `a.sum()`. For xarray, `a.sum()` skips NaNs by default, so it's equivalent to `np.nansum()` or `bottleneck.nansum()` (if bottleneck is installed).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,305373563
https://github.com/pydata/xarray/issues/1989#issuecomment-373219624,https://api.github.com/repos/pydata/xarray/issues/1989,373219624,MDEyOklzc3VlQ29tbWVudDM3MzIxOTYyNA==,1828519,2018-03-15T00:27:35Z,2018-03-15T00:27:35Z,CONTRIBUTOR,"Example:

```
import numpy as np
import xarray as xr
a = xr.DataArray(np.random.random((rows, cols)).astype(np.float32), dims=('y', 'x'))
In [65]: np.sum(a).data
Out[65]: array(499858.0625)

In [66]: np.sum(a.data)
Out[66]: 499855.19

In [67]: np.sum(a.data.astype(np.float64))
Out[67]: 499855.21635645436

In [68]: np.sum(a.data.astype(np.float32))
Out[68]: 499855.19
```

I realized after making this example that nansum gives expected results:
```
a = xr.DataArray(np.random.random((rows, cols)).astype(np.float32), dims=('y', 'x'))
In [83]: np.nansum(a.data)
Out[83]: 500027.81

In [84]: np.nansum(a)
Out[84]: 500027.81

In [85]: np.nansum(a.data.astype(np.float64))
Out[85]: 500027.77103802469

In [86]: np.nansum(a.astype(np.float64))
Out[86]: 500027.77103802469
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,305373563