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# G-Research tackles the biggest financial data challenges of tomorrow with Polars

**[Polars Blog](https://daily.dev/sources/polars)** · 3 min read · 0 upvotes · 0 comments

## Summary

G-Research, a quantitative finance research firm, shares testimonials from its machine learning engineers about switching from pandas to Polars for data processing. Users report significant speedups, including a 150x improvement in one case and a 20x speedup in dequantization, along with lower memory usage and a cleaner API. The firm highlights Polars' multi-threaded joins, responsive bug fixes from the development team, and improved developer experience compared to pandas, noting the library is now used across multiple internal projects including a plotting library.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pola.rs/posts/case-gresearch>

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---

Tags: [#python](https://daily.dev/tags/python), [#fintech](https://daily.dev/tags/fintech), [#data-engineering](https://daily.dev/tags/data-engineering), [#pandas](https://daily.dev/tags/pandas), [#polars](https://daily.dev/tags/polars)

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