issue_comments: 553940815

This data as json

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/508#issuecomment-553940815 https://api.github.com/repos/pydata/xarray/issues/508 553940815 MDEyOklzc3VlQ29tbWVudDU1Mzk0MDgxNQ== 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

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   98587746