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  • dcherian · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1144845488 https://github.com/pydata/xarray/issues/508#issuecomment-1144845488 https://api.github.com/repos/pydata/xarray/issues/508 IC_kwDOAMm_X85EPPSw dcherian 2448579 2022-06-02T13:10:04Z 2022-06-02T13:10:04Z MEMBER

Yes that is correct

 
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   Ignore missing variables when concatenating datasets? 98587746
553940815 https://github.com/pydata/xarray/issues/508#issuecomment-553940815 https://api.github.com/repos/pydata/xarray/issues/508 MDEyOklzc3VlQ29tbWVudDU1Mzk0MDgxNQ== dcherian 2448579 2019-11-14T15:33:52Z 2019-11-14T15:33:52Z MEMBER

Thanks for tackling this very important issue @scottcha ! from .dataarray import DataArray new_array = DataArray(coords=ds.coords, dims=ds.dims) ds[k] = new_array

Instead of creating a DataArray we only need to create a Variable (https://xarray.pydata.org/en/stable/internals.html#variable-objects).

I would instead try full_like(example_variable, fill_value=np.nan) (import full_like from the appropriate file). The trick would be figuring out what example_variable is. Maybe like this? (there may be some clever way to avoid the two loops)

``` python variables = [] for ds in datasets: if k in ds.variables: filled = full_like(ds.variables[k], fill_value=np.nan) break

for ds in datasets: if k not in ds.variables: variables.append(filled) else: variables.append(ds.variables[k])

vars = ensure_common_dims(variables) ```

Please send in a PR with any progress you make. We are happy to help out. We have some documentation on contributing and testing here: https://xarray.pydata.org/en/stable/contributing.html

 
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   Ignore missing variables when concatenating datasets? 98587746

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