by Ivano Malavolta and Karolina Bargieł

A research team of the VU Amsterdam published a paper benchmarking the energy usage and performance of pandas and Polars data analysis Python libraries.

by Isaac Robbins (Data Engineer) & Nelson Griffiths (Engineering & ML Lead) @ Double River Investments

Double River achieves 10x speedups and 50% memory reduction in their financial models utilizing Polars plugins.

by Polars Development Team

Polars now supports native reading from Hugging face datasets

by Polars dev team

This edition covers improved support for Hive partitioning, right joins, Hugging Face integration and much more.

by Ritchie Vink

We have released Python Polars 1.0. We are very excited to reach this milestone.

by Jean-Philippe Dubuc, Senior Data Engineer @ MDPI

MDPI, a pioneer in open access scientific publishing, uses Polars to process hundreds of GBs of textual data on their on-premise infrastructure on a daily basis.