Improving the quality of data visualizations can help in communicating results more clearly and transparently to other scientists, stakeholders and the general public. This course will use a workshop format to help students build their own data visualization projects using R, with Urban Health examples. This course will include a general introduction to basic data visualization concepts and best practices to generate static figures. This course will also cover basic concepts regarding interactive data visualization and spatial data. This course will provide all the required code, and some of the code may be useful to apply to your own visualizations with some adjustments. Thus, participants with a stronger R background will be able to create more complex visualizations. 

Last, each student will bring their own plotting project concept to receive feedback on it and work on the code needed to get a production quality figure.

After completing this course, participants will be able to:

• Understand the basic principles of data visualization
• Perform basic data management to get data ready for visualization using R
• Use the ggplot2 R package to plot high-quality figures
• Create animated plots, interactive web-plots using R, and map spatial data using R
• Convert research/advocacy ideas into effective plots, from data to code to plot

Prerequisite knowledge: Prior basic knowledge of R or concurrent enrollment in the “Intro to R” Summer Institute course taught by Brian Lee, PhD is required for this course. Advanced knowledge of R is not required for this course.