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Concretely I'm still waiting to be able to use the fix to this issue I reported 20 days ago :). I like your crate that's why I'm bringing up this issue as it is frustrating to see the python version having the fix while I need to use workarounds till the next version is released.
We didn't conduct our own benchmarks for this post, but in this comparison from ~1 year ago, Polars emerged as the fastest https://h2oai.github.io/db-benchmark/
However you cannot publish to crates.io, if any of your dependencies point to github. I don't think its too bad, because you as a rust use can always point to our master, until we issue a new release next month.
The best one I've found is plotnine, which is just a reimplementation of the ggplot API.
That said, one alternative I've seen that is compatible with Git is JJ which looks interesting. And Pijul may have a chance.
I've got to make a shameless plug for Explorer, which is a dataframe library for Elixir that builds on `polars`. It's not quite just bindings, as the idea is to have a functional, dplyr-esque API with pluggable backends (e.g. ExplorerSQL, ExplorerBallista). The main/default backend uses Elixir NIFs via Rustler to call polars.
Well, MS on the other hand created a fork/tool adding VFS support to Git: https://github.com/microsoft/VFSForGit and it seemed to have worked out for them. It is sort of a hack, but just shows that Git has had enough momentum to justify this hack, instead of going with some better suited alternative tools.
For the Raku language, a data analytics module can help us be more useful to data scientist / programmers. Polars is a better option than Pandas. Why?