When you're staring down a CSV file with billions of rows that won't fit in RAM, this is your way out. Vaex handles out-of-core DataFrames through memory-mapped HDF5 and Arrow files, letting you filter, aggregate, and visualize datasets at a billion rows per second on a single machine. The virtual columns are clever since they compute on the fly without eating memory, and the lazy evaluation means you can chain operations without waiting. It's not as fast as Polars if your data fits in RAM, and it's not distributed like Dask, but for single-machine analytics on tabular data that exceeds your memory, it hits a sweet spot that the other tools don't really cover.
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill vaex