issues: 1381955373

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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
1381955373 I_kwDOAMm_X85SXvct 7065 Merge wrongfully creating NaN 12760310 closed 0     9 2022-09-22T07:17:58Z 2022-09-28T13:16:13Z 2022-09-22T13:28:17Z NONE      

What happened?

I'm trying to merge the following datasets, which have exactly the same coordinates and extents (not sure why it could cause any conflict).

After merging them, with xr.merge([ds, alt]) (the order does not matter), the resulting altitude has NaNs all over the place. I could tell that something wrong was going on because the merge took too long (about 30s, while it should be pretty much instantaneous given the dimensions).

Here is a comparison of the altitude before and after the merge

If I try to create the DataArray manually, that is

python ds['altitude'] = xr.DataArray(data=alt.altitude.values, dims=("lat","lon")) everythign works fine.

What did you expect to happen?

Normal broadcasting rules should apply and the resulting array should not have NaNs.

Minimal Complete Verifiable Example

No response

MVCE confirmation

  • [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:43:44) [Clang 13.0.1 ] python-bits: 64 OS: Darwin OS-release: 21.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.8.1 xarray: 2022.6.0 pandas: 1.5.0 numpy: 1.22.4 scipy: 1.9.1 netCDF4: 1.6.1 pydap: None h5netcdf: None h5py: 3.7.0 Nio: None zarr: 2.12.0 cftime: 1.6.2 nc_time_axis: None PseudoNetCDF: None rasterio: 1.3.2 cfgrib: 0.9.10.1 iris: None bottleneck: 1.3.5 dask: 2022.9.1 distributed: 2022.9.1 matplotlib: 3.6.0 cartopy: 0.21.0 seaborn: 0.12.0 numbagg: None fsspec: 2022.8.2 cupy: None pint: 0.19.2 sparse: None flox: None numpy_groupies: None setuptools: 65.3.0 pip: 21.3.1 conda: None pytest: None IPython: 8.5.0 sphinx: None 
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   completed 13221727 issue

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