Declarative Data Visualization with Vega-Lite & Altair
Declarative Data Visualization with Vega-Lite & Altair

Abstract: 

In this workshop, we will introduce the concepts of declarative data visualization, which are widely used by the Jupyter and Observable data science communities, and companies such as AirBnB, Apple, Elastic, Google, Microsoft, Netflix, Twitter, and Uber. You will learn the basic vocabulary for grammar of data visualizations and learn how to use this vocabulary to author interactive plots via declarative visualization libraries including Vega-Lite (in JavaScript) and Altair (in Python). With these libraries, users can rapidly and concisely create rich interactive visualizations. For example, brushing & linking among scatterplots and interactive cross filtering require only a few lines of code in Vega-Lite, versus hundreds in D3.

We will first introduce the basics of Vega-Lite and Altair including how to create simple single-view plots, how to combine them into layered plots and multi-view dashboards, and how to make them interactive. In addition, we will highlight latest new features in Vega-Lite and Altair 4.

We will also describe how to use them for various use cases such as exploring data, customizing plots for sharing and publication, building web applications, as well as automatically generating charts on a server. Finally, we will illustrate how Vega-Lite and Altair fit into a larger ecosystem of data visualization tools.

There are no formal requirements to attend this tutorial, besides excitement about creating visualizations—though some previous experience building visualizations will help you get the most out of the experience.

Bio: 

Kanit (Ham) Wongsuphasawat is a research scientist at Apple where he works on data visualization tools and human-centered machine learning. Kanit holds a PhD in Computer Science from the University of Washington (UW), where he worked with Jeffrey Heer and the Interactive Data Lab. Systems he developed have won awards at premier academic venues, and are used by the leading data science communities (e.g., Jupyter and Observable) and leading tech companies including AirBnB, Apple, Google, Microsoft, Netflix, and Twitter.