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/1346#issuecomment-290755867,https://api.github.com/repos/pydata/xarray/issues/1346,290755867,MDEyOklzc3VlQ29tbWVudDI5MDc1NTg2Nw==,5852283,2017-03-31T16:07:56Z,2017-03-31T16:07:56Z,CONTRIBUTOR,"I think this might be a problem with bottleneck? My interpretation of _create_nan_agg_method in xarray/core/ops.py is that it may use bottleneck to get the mean unless you pass skipna=False or specify multiple axes. And,

```python
In [2]: import bottleneck
In [3]: bottleneck.__version__
Out[3]: '1.2.0'

In [6]: bottleneck.nanmean(ds.var167.data)
Out[6]: 261.6441345214844
```

Forgive me if I'm wrong, I'm still a bit new.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,218459353
https://github.com/pydata/xarray/issues/1346#issuecomment-290747253,https://api.github.com/repos/pydata/xarray/issues/1346,290747253,MDEyOklzc3VlQ29tbWVudDI5MDc0NzI1Mw==,5852283,2017-03-31T15:38:12Z,2017-03-31T15:53:07Z,CONTRIBUTOR,"Also on macOS, and I can reproduce.

Using python 2.7.11, xarray 0.9.1, dask 0.14.1 installed through Anaconda. I get the same results with xarray 0.9.1-38-gc0178b7 from GitHub.

```python
In [3]: ds = xarray.open_dataset('ERAIN-t2m-1983-2012.seasmean.nc')

In [4]: ds.var167.mean()
Out[4]:
<xarray.DataArray 'var167' ()>
array(261.6441345214844, dtype=float32)
```

Curiously, I get the right results with skipna=False...

```python
In [10]: ds.var167.mean(skipna=False)
Out[10]:
<xarray.DataArray 'var167' ()>
array(278.6246643066406, dtype=float32)
```

... or by specifying coordinates to average over:

```python
In [5]: ds.var167.mean(('time', 'lat', 'lon'))
Out[5]:
<xarray.DataArray 'var167' ()>
array(278.6246643066406, dtype=float32)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,218459353