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/3080#issuecomment-508833311,https://api.github.com/repos/pydata/xarray/issues/3080,508833311,MDEyOklzc3VlQ29tbWVudDUwODgzMzMxMQ==,5852283,2019-07-05T18:23:03Z,2019-07-05T18:23:03Z,CONTRIBUTOR,"I think you're right, this is nearly the same issue as #2850. Your dataset has an attribute named _NCProperties which is one of the [hidden/forbidden attributes](https://www.unidata.ucar.edu/software/netcdf/docs/file_format_specifications.html#atts_spec).
If I remove the attribute:
`del dsSel.attrs['_NCProperties']`
`dsSel.to_netcdf(outnc)` then works for me with no errors.
You can also delete the attribute on `ds` instead and subsequent selections should also work.
As an aside, if I run
`ncdump -h https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/dodsC/birdhouse/cccs_portal/indices/Final/BCCAQv2/tg_mean/YS/rcp26/simulations/BCCAQv2+ANUSPLIN300_bcc-csm1-1_historical+rcp26_r1i1p1_1950-2100_tg_mean_YS.nc `
""_NCProperties"" doesn't show up in the attributes, but I assume this is because ncdump hides it and not because it gets added by xarray or netcdf4. If that's not the case it could be a bug in xarray or netcdf4. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,464315727
https://github.com/pydata/xarray/pull/3028#issuecomment-504078924,https://api.github.com/repos/pydata/xarray/issues/3028,504078924,MDEyOklzc3VlQ29tbWVudDUwNDA3ODkyNA==,5852283,2019-06-20T15:46:59Z,2019-06-20T15:46:59Z,CONTRIBUTOR,Sounds great. Thanks for making this a smooth and well documented process for new contributors ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,456971151
https://github.com/pydata/xarray/pull/3028#issuecomment-503553184,https://api.github.com/repos/pydata/xarray/issues/3028,503553184,MDEyOklzc3VlQ29tbWVudDUwMzU1MzE4NA==,5852283,2019-06-19T13:08:41Z,2019-06-19T13:08:41Z,CONTRIBUTOR,"I have to say as someone who is probably an average user, inconsistencies between related projects, like xarray/pandas or matplotlib/seaborn, drive me nuts. But I also agree that `missing=` is more descriptive, and if we were starting from scratch I would totally support that. So I will defer to the maintainers here. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,456971151
https://github.com/pydata/xarray/issues/2770#issuecomment-464088384,https://api.github.com/repos/pydata/xarray/issues/2770,464088384,MDEyOklzc3VlQ29tbWVudDQ2NDA4ODM4NA==,5852283,2019-02-15T15:22:48Z,2019-02-15T15:22:48Z,CONTRIBUTOR,"I can reproduce OP when the coordinate is a datetime64, but the problem does not occur with int64s (or float64s).
datetime coordinate:
```
In [1]: import xarray
In [2]: xarray.__version__
Out[2]: '0.11.2'
In [3]: import datetime as dt
In [4]: da = xarray.DataArray([0], coords=[('time', [dt.datetime(1979, 1, 1)])])
In [5]: da.isel(time=0).time.count()
Out[5]:
array(-1)
Coordinates:
time datetime64[ns] 1979-01-01
```
int coordinate:
```
In [6]: da = xarray.DataArray([0], coords=[('time', [0])])
In [7]: da.isel(time=0).time.count()
Out[7]:
array(1)
Coordinates:
time int64 0
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,409906674
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]:
array(261.6441345214844, dtype=float32)
```
Curiously, I get the right results with skipna=False...
```python
In [10]: ds.var167.mean(skipna=False)
Out[10]:
array(278.6246643066406, dtype=float32)
```
... or by specifying coordinates to average over:
```python
In [5]: ds.var167.mean(('time', 'lat', 'lon'))
Out[5]:
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