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What behaviour would you expect these functions to have in H3-Pandas?
compact and uncompact are set operations and applying them to a dataframe with potential additional data is not straightforward. I see two general options
The data would have to be removed and the returned dataframe would be index-only. This would not be difficult to implement. I can see how that's still potentially convenient, as it allows you to string further h3 operations.
The compacted/uncompacted cells would have to be matched back with the rows they originated from with some (dis)aggregation operation being performed on the data. k_ring_smoothing does something similar.
It would be helpful if you could elaborate on your usecase to drive the potential API.
I'm working with polygons, primarily categorical data (geology, rock type, formation name, descriptions etc).
I'm using polyfill / polyfill_resample, however it's resulting in massive numbers of polygons to accurately represent the input geometries - resolution 13 or 14 required.
I could do with the compact function at the end to simplify the data to fewer features using an index attribute eg rock type.
Hi,
This library is great! Do you have plans to implement the H3 compact and uncompact functions?
Regards,
Edd
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