Abstract
Polars is the new dataframe on the block taking the world by storm.
You'll learn:
- what Polars is, and what it can do for you
- Polars basics and core concepts (including expressions and lazy computation)
- how to work with different datatypes, and how the List datatype gives you superpowers
- interoperability with other tools: NumPy, SciPy, Arrow, pandas, Numba
- migrating from pandas
What better way to learn it than by attending a PyCon Lithuania tutorial, delivered by a Polars core dev?
Description
This will be a hands-on tutorial with many practical examples. It is aimed at software professional working with data who want to level up their skills with learning modern tools.
The format will be roughly:
Intro
- Motivation, what Polars can do for you
- Round of introductions, get some requests for what you'd like to get out of the session, and what you'd like Polars to do for you
Part 1: basics
We'll cover core concepts:
- creating dataframes
- column operations
- row operations
- expressions
- migration from pandas
- lazy execution
- how to avoid "shooting yourself in the foot" with Polars lazy execution
Part 2: namespaces
- working with strings
- working with datetimes
- nested datatypes, and how the list datatype gives you superpowers
- enums vs categoricals
- how you can add your own namespace (but why you might not want to)
Part 3: when Polars isn't enough:
- interoperability with NumPy / SciPy / Arrow / pandas
- using Numba for fast user-defined functions
- how to learn to write a Polars Plugin in Rust. We won't have time to learn Rust in this tutorial, but you'll be shown where to turn to, and how to learn just enough Rust so that you can write your own Polars Plugin.
- Conclusion, free-form Q&A, assorted requests
By the end of the session, you'll have gained experience with Polars and will know where to turn to for practically any problem you'd like to solve with it.
