Expressive and Fast Dataframes in Python with Polars || Juan Luis

The outline of the talk goes as follows: -We will make a very brief introduction to pandas, we will talk about its importance, and we will point out some of its shortcomings (as its own creator did half a decade ago (10 minutes) -We will enumerate some of the current pandas alternatives and classify them (pandas-like vs bespoke, single-node vs distributed) (5 minutes) -We will do a live demo of how to analyze and manipulate a relatively big dataset using Polars inside Orchest Cloud y and showcase some of its unique capabilities (20 minutes). -Recommendations and conclusions (5 minutes). After the talk, you will have more information on how some of the modern alternatives to pandas fit into the ecosystem, and will understand why Polars is so exciting and promising. Prior exposure to data manipulation with Python (not necessarily with pandas) will help make the most of the presentation. The talk will build upon this blog post about Polars. PUBLICATION PERMISSIONS: PyData Organizer provided Coding Tech with the permission to republish PyData talks. CREDITS: PyData YouTube channel: @PyDataTV