Data Visualization in Policy

3 Credits · Level: Undergraduate

This course introduces students to visual methods of discovering and communicating public policy and politics insights from data. Students will learn to interpret, evaluate, and create data visualizations and graphics using primarily R, a popular open-source programming language. Students will also build their intuition regarding quantitative analysis, data cleaning, and data exploration. The course highlights the use of Wilkinson’s grammar of graphics as implemented in R as well as some R packages for specialized visualizations. Despite the focus on R as a data visualization tool, the course also emphasizes creative problem solving and general principles that apply to most data visualization platforms. This is an active learning course. Students will work individually and collaboratively to consider subjective design tradeoffs and existing research on visualization best practices, and how to use technical skills to implement these principles. By the end of the semester, each student will create an aesthetically compelling and analytically sound visualization portfolio; students are encouraged to focus on their own policy areas of interest where applicable when completing assignments. No prior experience with R or coding is required. All students should be prepared to bring a laptop to each class session. Pre-requisites: PPOL 3000 or permission of the professor.