Ivan Ruiz Manuel

> @irm-codebase and @tud-mchen6 maybe we can discuss the design briefly after the group meeting today? @brynpickering may be useful to include in the discussion. That would be good! No...

Relatively big update to this PR to fix #346. This was necessary because #354 made our pandas code go at a snail's pace. Moving to `xarray` was more efficient than...

@brynpickering updated to the newest JRC version (checksum passed, no difference :+1: ) I had to modify a couple of lines at the JRC level because the production dataset did...

@brynpickering added most of your suggestions, with the exception of the gap filling test. Let me know if you find anything else during review. Otherwise, I'll merge this in and...

@timtroendle I'd say that adding full documentation now is only additional overhead: this is only part of the module (we are still missing other industry and chemical industry), plus disaggregation,...

> Isn't that solved via running `snakemake --cleanup-metadata data/automatic/**/*` ? I think this was added in the documentation FAQ recently by @brynpickering Thanks, I was not aware of that! Still,...

Took a bit to arrive to a test case that made sense... I think you are right: it's mostly due to updates to the environments (specially for industry, since the...

This PR now integrates the JRC module code and `xarray` processing. Also, I've added some quality of life processing for "other industries": - You can now "turn off" the processing...

@brynpickering I've implemented your comments, and a couple of extras. The biggest updates are: - improved names of stuff to reduce ambiguity - standardized naming from "sector" to "category" to...

@timtroendle quick fix for the `assert` case you mentioned. I also updated the name of the files, to make them match the category (did not do it before to avoid...