827: Polars: Past, Present and Future, with Polars Creator Ritchie Vink

Ritchie Vink, CEO and Co-Founder of Polars, Inc., speaks to Jon Krohn about the new achievements of Polars, an open-source library for data manipulation. This is the episode for any data scientist on the fence about using Polars, as it explains how Polars managed to make such improvements, the APIs and integration libraries that make it so versatile, and what’s next for this efficient library. This episode is brought to you by epic LinkedIn Learning instructor Keith McCormick, by Gurobi, the Decision Intelligence Leader, and by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: Why Polars is so efficient [05:20] Polars’ easy integration with other data-processing tools [21:23] Eager vs lazy executive in Polars [32:15] Polars’ data processing of large- and small-scale datasets [38:28] Ritchie’s plans to scale his company [46:14] Upcoming features in Polars [58:06] Additional materials: www.superdatascience.com/827

Om Podcasten

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.