Analyze your data at the speed of light with Polars and Kedro
Room: Saphire C - Web Dev
Time: 11:00 - 11:55
Writing maintainable data science code is a big topic, and different people have different opinions on the best ways to do it. Wouldn't it be nice if there was an opinionated framework to set some structure and help data scientists be more effective and ship their analysis and models to production faster? In this workshop we present Kedro, an opinionated Python framework for creating reproducible, maintainable and modular data science code. We will also show how you can combine it with Polars, a new dataframe library backed by Arrow and Rust, for lightning fast data manipulation and exploratory data analysis.
Juan Luis Cano Rodríguez
Juan Luis (he/him/él) is an Aerospace Engineer with a passion for STEM, programming, outreach, and sustainability. He works as Developer Advocate for Kedro, an opinionated data science framework, at QuantumBlack, AI by McKinsey. He has worked as Developer Advocate at Read the Docs, as software engineer in the space, consulting, and banking industries, and as a Python trainer for several private and public entities. Apart from being a long-time user and contributor to many projects in the scientific Python stack (NumPy, SciPy, Astropy) he has published several open-source packages, the most important one being poliastro, an open-source Python library for Orbital Mechanics used in academia and industry. Finally, Juan Luis is the founder and former chair of the Python España association, the point of contact for the Spanish Python community, former organizer of PyCon Spain, which attracted 800 attendees in its last in-person edition in 2022, and current organizer of the PyData Madrid monthly meetups.