When I started reading about pandas complexity and the smaller set of operations needed, couldn't help but think of R's data.table simplicity.

Granted, it's got more than 15 functions, but its simplicity seems to me very similar to what the author presented in the end.

Back when I used to use Stackoverflow, someone would always come along with a data.table solution when I asked a question about dplyr. The terse syntax seemed so foreign compared to the obvious verb syntax of dplyr. But then I learned data.table and I've never looked back. It's a superb tool!

data.table "simplicity" is actually a huge set of features, they just have a clever and compact way to express those features in code. At the same time, there is effectively no standard-eval programmatic interface for it, which makes it a headache for building programs rather than scripting with. data.table is amazing, but it is anything but simple IMO.

This reminded me of this arxiv paper on the self replication capabilities of some AI models: [https://arxiv.org/abs/2412.12140](https://arxiv.org/abs/2412.12140)