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
841012076,MDU6SXNzdWU4NDEwMTIwNzY=,5075,Losing data when add a raster to a dataset,18444902,open,0,,,13,2021-03-25T14:54:05Z,2021-05-05T15:40:30Z,,NONE,,,,"As I mentioned [here](https://github.com/corteva/geocube/issues/62), when I add a raster inside a [geocube](https://github.com/corteva/geocube) are produced a lot of nodata.

After a test @snowman2 has [indicates](https://github.com/corteva/geocube/issues/62#issuecomment-806283019) that this is a possible bug of xarray libraries.

> I was able to reproduce the issue you demonstrated. I think it has to do with decimal precision of the coordinates when adding the DataArray to the Dataset. That being said, I checked that the `x` coordinate and `y` coordinates were the exact same for `raster_in` and `out_grid`. This is likely an issue with `xarray` and not `geocube`.
> 
> For a workaround, this got it working without the gaps for me:
> 
> ```python
> import geopandas
> import rioxarray
> from geocube.api.core import make_geocube
> 
> vector_in = geopandas.read_file(""vector_data.shp"")
> raster_in = rioxarray.open_rasterio(""raster_data.tif"", masked=True).sel(band=1).drop(""band"")
> 
> out_grid = make_geocube(
>     vector_data=vector_in,
>     measurements=[""id""],
>     like=raster_in,
> )
> 
> out_grid[""process_value""] = (raster_in.dims, raster_in.values, raster_in.attrs, raster_in.encoding)
> ```

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