Pandas vs Polars in 2025: Choosing the Best Python Tool for Big Data

This content originally appeared on HackerNoon and was authored by Dave Jodhan

This article compares the performance of Pandas and Polars, two Python libraries for data analysis, by running benchmarks on a synthetic 6-million-row dataset. While both libraries offer similar functionality for filtering, arithmetic, and string manipulation, Polars significantly outperforms Pandas in native operations, delivering up to 99% faster processing times. However, for custom Python functions or compatibility with third-party tools, Pandas still holds its ground. The piece concludes with practical guidelines on when to use each library based on speed, syntax complexity, and interoperability.

This content originally appeared on HackerNoon and was authored by Dave Jodhan