What you'll learn

Python analysts often hit performance and scalability limits when working with pandas or shifting too early to heavier tools like Spark. In this course, Up and Running with Polars, you’ll gain the ability to use Polars to perform efficient, expression-driven data analysis workflows. First, you’ll explore what Polars is, where it fits in the data ecosystem, and how it compares to pandas, SQL-based workflows, and distributed engines. Next, you’ll discover Polars’ core concepts, including expressions, eager vs. lazy execution, and its DataFrame and Series objects and how analysts typically use them in practice. Finally, you’ll learn how to load data, explore schemas, apply expressions, build lazy pipelines, and create grouped summaries using Polars. When you’re finished with this course, you’ll have the skills and knowledge of Polars needed to confidently decide when to use it and to complete a basic end-to-end analysis workflow efficiently.