Practical, code-first guides to the Polars DataFrame library — the fast Rust-backed alternative to pandas.
Connect with usPolars is a fast, multi-threaded DataFrame library written in Rust with a Python API. If you've felt pandas slow down on bigger datasets, Polars is the upgrade path — same shape of API, dramatically better performance, and a query optimiser baked in.
These tutorials are written in the same Minimal Viable Analytics style I use with clients: each one focuses on a single core operation — filtering, sorting, grouping, joining, creating columns, plotting — with working Python you can copy straight into a notebook. If you're new to Polars, start with filtering and work down. If you're already comfortable, jump to whichever operation you need.
The Learn Polars page runs the same six skills as runnable browser examples — great if you want to play with the code before reading the deep dives.
