The syllabus for the course, along with discussions about "what" visualizations are, and how to orient yourself in the course.
IS445 - Data Viz - BOG-BOU
This is the course website for 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
What are some of the basics of how we interpret visualizations? How can we describe the process of making choices, understanding our audience, and so forth?
How do we store and draw data?
When we draw something on a screen, how do we represent that internally, and how is that translated into pixels? How are values transformed from 0's and 1's into values we can manipulate and understand?
Data Manipulation and Distributions
What operations can we do on data, how can we represent and compute distributions, and how do we scale values in relation to each other?
How do we transform and scale data? How can we apply scalings to data, and what does this have to do with color?
How do colors work? What are the different ways we can map colors to values? What should we keep in mind when doing this?
Week 4
Basics of Interaction and Engines of Visualization
traitlets interactivity ipywidgets jupyter bqplot
Widgets and Traitlets for Interactivity
We talk about the basics of using Traitlets and data binding in visualization.
We introduce the basics of bqplot
Week 5
Exploring More Interactivity
interactivity concepts bqplot vega-lite web javascript github-pages
The foundations of interactivity, and how we can think about it and how we use it.
We introduce a little bit of javascript, how to publish websites on GitHub, and we start learning vega-lite.
Viz Platforms and more Vega-lite
We go over more details of using vega-lite and how to embed vega-lite visualizations in a web page.
We talk about putting together the process of prototyping a visualization, preparing data for it, and then putting that visualization on a website.
Today we'll cover some time-series axes, use bqplot to display a Map and talk about how to use Pandas for time-series data.
Today we'll talk about map projections, how to properly wrap a baseball, and continue with our dashboarding.
Subselection, Layouts and Dashboards
Today we'll talk about map projections, how to properly wrap a baseball, and continue with our dashboarding.
Today we'll start talking about the platform Iodide, and using it as a way to explore javascript and python
We'll discuss a bit about updating vega-lite visualizations using their API in Iodide, and we'll move on to looking at GeoJSON data in Jupyter and what it looks like.
Types of Visualization Audiences
What are the different audiences you might have for visualizations? How can we tune our visualizations to those audiences?
Basics of Scientific Visualization
What makes scientific data "different"?
This week we introduce concepts from D3, including data binding, thinking about the document object model, and how to set up a D3 playground.
This week we talked about using D3 for transitions, interaction, and we started sketching out our final project.
This week we talked about using D3 for transitions, interaction, and we started sketching out our final project.
This week, we tried bringing it all together: let's talk about dashboards in Jupyter, and we'll explore Gaia eDR3 data using the tools in our toolbox.