Data visualization

Overview

Visualizations are a key form of communication. Data visualizations let data “speak” to an audience. The story they tell and the message they convey may or may not be interesting, important, and successful; the design of the visualizations themselves plays an essential role in their impact.

In this course, we’ll learn basic design principles, the building blocks of successful charts, as well as the coding necessary to produce such charts. By the end of the course you will have become both a critical consumer of data visualization and a producer of attractive, informative, and honest (as in not misleading) charts, in a wide range of forms.

Producing good visualizations can be immensely satisfying, but also quite frustrating. We’ll work together to keep the amount of frustration to a minimum. Mastering the course material should be rewarding and even fun!

To become a confident producer of successful visualizations, you need to master a programming vocabulary. Two of the most common languages for data visualization are R and python. R is more commonly used by social scientists; python by those with a computational background. This course is agnostic about which you prefer. All in-class examples, assignments, etc. can be done equally well in R and python. You can do all your work in one language or go back and forth between languages — the choice is yours.

Syllabus

I most recently offered this course in the Fall of 2023. Syllabus here