#Polars #DataFrame #OpenSourceSoftware Polars, Python, Narwhals, Rust, and Pandas: Marco Gorelli talks to @JonKrohnLearns 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: • [00:00:00] Introduction • [00:06:35] When to use Polars vs Pandas • [00:18:24] How Polars optimizes string operations and data processing • [00:46:32] Where Narwhals outstrips Polars and Pandas • [00:53:23] The benefits of using Altair • [01:08:02] Addressing the lack of women in data science • [01:15:11] How to win a forecasting competition Additional materials: https://www.superdatascience.com/815