issues: 383844989

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
383844989 MDU6SXNzdWUzODM4NDQ5ODk= 2566 Unexpected warning when taking mean of all-NaN slice in chunked DataArray 30007270 closed 0     2 2018-11-23T14:33:00Z 2020-10-24T04:17:32Z 2020-10-24T04:17:32Z NONE      

Problem description

When taking the mean of a DataArray with an all-NaN axis, I get the following warning: ``` data = np.array([[np.nan,0],[np.nan,1]]) xc = xr.DataArray(data).chunk() xc.mean('dim_0').compute()

/nbhome/xrc/anaconda2/envs/py361/lib/python3.6/site-packages/dask/array/numpy_compat.py:28: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)

<xarray.DataArray (dim_1: 2)> array([ nan, 0.5]) Dimensions without coordinates: dim_1 ``` This confused me because the warning suggests a 0/0 division and/or issues with typecasting. Furthermore, the warning is different when the data is not chunked:

```python

x = xr.DataArray(data) x.mean('dim_0')

/nbhome/xrc/anaconda2/envs/py361/lib/python3.6/site-packages/xarray/core/nanops.py:161: RuntimeWarning: Mean of empty slice return np.nanmean(a, axis=axis, dtype=dtype)

<xarray.DataArray (dim_1: 2)> array([ nan, 0.5]) Dimensions without coordinates: dim_1

Also, using pure dask does not raise this warning. xd = da.from_array(data,chunks=(1,1))

xd.mean(axis=0).compute()

array([ nan, 0.5]) ```

Expected Output

Either the warning from a non-chunked DataArray or no warning would be preferred.

Output of xr.show_versions()

commit: None python: 3.6.6.final.0 python-bits: 64 OS: Linux OS-release: 2.6.32-696.30.1.el6.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US LOCALE: en_US.ISO8859-1 xarray: 0.11.0 pandas: 0.23.4 numpy: 1.13.1 scipy: 0.19.1 netCDF4: 1.3.1 h5netcdf: 0.5.0 h5py: 2.7.1 Nio: None zarr: None cftime: 1.0.2.1 PseudonetCDF: None rasterio: None iris: None bottleneck: 1.2.0 cyordereddict: None dask: 0.20.1 distributed: 1.24.0 matplotlib: 3.0.1 cartopy: 0.16.0 seaborn: 0.8.1 setuptools: 35.0.2 pip: 18.1 conda: None pytest: 3.0.7 IPython: 6.5.0 sphinx: None 
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