issues: 432074821

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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
432074821 MDU6SXNzdWU0MzIwNzQ4MjE= 2889 nansum vs nanmean for all-nan vectors 10194086 closed 0     3 2019-04-11T15:04:39Z 2022-01-05T21:59:48Z 2019-04-11T16:08:02Z MEMBER      

```python import xarray as xr import numpy as np

ds = xr.DataArray([np.NaN, np.NaN])

ds.mean() ds.sum()

```

Problem description

ds.mean() returns NaN, ds.sum() returns 0. This comes from numpy (cp np.nanmean vs. np.nansum), so it might have to be discussed upstream, but I wanted to ask the xarray community first on their opinion. This is also relevant for #422 (what happens if the all weights are NaN or sum up to 0).

Expected Output

I would expect both to return np.nan.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 23:01:00) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.4.176-96-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.12.1 pandas: 0.24.2 numpy: 1.16.2 scipy: 1.2.1 netCDF4: 1.5.0.1 pydap: None h5netcdf: 0.7.1 h5py: 2.9.0 Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: 1.2.0 PseudonetCDF: None rasterio: 1.0.22 cfgrib: None iris: None bottleneck: 1.2.1 dask: 1.1.5 distributed: 1.26.1 matplotlib: 3.0.3 cartopy: 0.17.0 seaborn: 0.9.0 setuptools: 41.0.0 pip: 19.0.3 conda: None pytest: 4.4.0 IPython: 7.4.0 sphinx: 2.0.1 
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   completed 13221727 issue

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