Polars, Python, Narwhals, Rust, and Pandas: Marco Gorelli talks to Jon Krohn about the many ways to use the newest data libraries available, the joys of open-source development, and the best method to win prizes in forecasting competitions.

This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0), by Babbel (https://www.babbel.com/superdata), the science-backed language-learning platform, and by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists), the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• When to use Polars vs Pandas [08:26]
• How Polars optimizes string operations and data processing [20:08]
• Where Narwhals outstrips Polars and Pandas [48:37]
• The benefits of using Altair [55:21]
• Addressing the lack of women in data science [1:09:58]
• How to win a forecasting competition [1:16:58]

Additional materials: www.superdatascience.com/815

The Super Data Science Podcast: Machine Learning | AI | Success

815: Polars: Faster DataFrame Ops, with Marco Gorelli

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.

New tracks tagged #Data Libraries