885: Python Polars: The Definitive Guide, with Jeroen Janssens and Thijs Nieuwdorp
May 6, 2025
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Jeroen Janssens, a Senior Developer Relations Engineer at Posit and author, teams up with Thijs Nieuwdorp, a data scientist at Zomnia, to discuss their book on the Polars library. They dive into why data scientists are migrating from Pandas to Polars, highlighting its efficiency in memory usage and processing speed. The duo shares best practices for using Polars, the benefits of collaboration with NVIDIA and Dell, and the transformative impact of the Great Tables package on data presentation. Their insights will leave you eager to enhance your data manipulation skills!
The growing popularity of Python Polars over Pandas is fueled by its declarative syntax, leading to more readable and maintainable code.
Jeroen Janssens and Thijs Nieuwdorp's writing journey for 'Python Polars: The Definitive Guide' involved overcoming initial rejections and embracing personal growth.
Real-world implementations, such as at Aliander, showcased Polars' efficiency by drastically reducing memory usage and enhancing processing capabilities.
Deep dives
Python Polars: A Rising Star in Data Frames
The episode highlights the increasing popularity of Python Polars, a high-performance data frame library gaining traction among users traditionally reliant on Pandas. Key reasons for this shift include Polars' declarative syntax, allowing users to express desired outcomes rather than specify procedural commands. This results in more readable code and significantly reduced complexity, as well as easier debugging. Additionally, the increasing number of GitHub stars for Polars indicates its rapid adoption, suggesting it may soon surpass Pandas in user preference.
The Journey of Writing Python Polars: The Definitive Guide
Jeroen Janssens and Thijs Newdorp discuss their experience in writing 'Python Polars: The Definitive Guide', elaborating on their motivations and the challenges they faced during the writing process. Initially, their proposal for the book faced rejection from O'Reilly Publishing, leading them to create a more comprehensive and detailed submission that included statistics and potential use cases. They also reflected on the personal growth achieved through the writing process, acknowledging that imposter syndrome is common among authors. Ultimately, their collaboration has proven beneficial as they navigated the complexities of documenting Polars effectively.
Real-World Applications and Benchmarking of Polars
A significant discussion in the episode centers around real-world implementations of Polars, particularly at Aliander, a Dutch power grid provider. The team effectively utilized Polars to optimize their codebase, achieving a remarkable reduction in memory usage from 500 gigabytes to just 40 gigabytes. This drastic improvement enabled them to enhance their processing capacity, achieving faster computations without the need for expensive hardware upgrades. The conversation emphasizes how practical experience with Polars not only assisted in shaping the book but also highlighted its capabilities in production environments.
Innovative Collaborations: The Role of Dell and NVIDIA
The authors recount an exciting collaboration with Dell and NVIDIA that allowed them to conduct comparative benchmarks for their book. Utilizing NVIDIA's cutting-edge GPU technology, they were able to explore the performance benefits of running Polars on GPUs versus CPUs. The partnership proved beneficial in generating credible performance metrics, as they actively benchmarked various NVIDIA cards within a robust Dell setup. This collaboration reflects the synergy between innovative technology and practical application in data science.
The Evolution of Visualization in Polars
The episode concludes with engaging anecdotes about the evolution of data visualization components within Polars. Following a suggestion to include a chapter on data visualization, the authors ended up rewriting significant content due to a shift in recommended libraries, showcasing the collaborative nature of open-source projects. They emphasized the need to keep chapters updated with evolving technologies while ensuring educational content remains relevant. The integration of libraries like Altair and Great Tables highlights the authors' commitment to providing comprehensive resources for users seeking effective visualization techniques.
Jeroen Janssens and Thijs Nieuwdorp are data frame library Polars’ greatest advocates in this episode with Jon Krohn, where they discuss their book, Python Polars: The Definitive Guide, best practice for using Polars, why Pandas users are switching to Polars for data frame operations in Python, and how the library reduces memory usage and compute time up to 10x more than Pandas. Listen to the episode to be a part of an O’Reilly giveaway!
