The syllabus for the course, what we're going to talk about, and some intro to p5js.
IS545 - Spring 2022
This is the course website for Advanced Data Visualization, instructed by Matthew Turk (mjturk@illinois.edu).
Below, you will find the materials for each week, as well as the syllabus that includes contact information and a course outline.
Lectures and Materials
We dig a little bit deeper into p5js, showing how to rotate, translate, and push/pop matrix transformations. We'll also take a look at getting input from a webcam and from input elements.
Big things, small things, and showing the difference.
Digging into matplotlib as a canvas
Getting Started with Interactivity
Getting started with interactivity and bqplot
Web Viz, the Browser, and Interactivity
Getting started with interactivity and bqplot
Getting started with vega-lite
What are transformations, and how do we apply these to colors?
What are some ways to publish our visualizations on the web?
This week, we're going to start bringing together everything we've covered so far, and talk about what to do when we bump against the boundaries of these techniques.
Brushing, Responsivity and More
Today we start adding more interactivity to our trees and talk about some speed strategies
This lecture starts the process of exploring OpenGL-type concepts for rendering, why we might be interested in using them, and how we can apply them to visualizations.
What else can we do with vega-lite?
This lecture starts the process of exploring OpenGL-type concepts for rendering, why we might be interested in using them, and how we can apply them to visualizations.
Building on what we did last time, we'll connect DeckGL visualizations to visualizations in bqplot.
We're going to dig much deeper into matplotlib, starting with styles, moving on to how patches are placed on an image, and then start talking about how we can package up our custom routines for reuse.
We learned about creating packages, reusability, and then applied this to a Ticket to Ride visualization project.
Week 11
Server-based Visualizations
getting-help assignment-follow-up servers jupyter-extensions flask streamlit dash
We'll talk about how you can "get help" from online sources, and then move on to server-side visualizations.
First we'll go through some basics of how web applications work, and write our own Hello World flask app. Then we'll look at two frameworks for server-side visualizations.
Today we discussed streamlit and explored how to use it to connect the data visualizations we have been building this semester.
We briefly cover some concepts in scientific visualization, and why they're different from the other types of visualization we've discussed.
We briefly cover some concepts with Explorable Explanations and platforms for them.