Data Visualization

Course Outline and Readings


For each class, we will spend the first half of class discussing general principles of data visualization. The second half of each class we'll spend working on programming, with an assignment that you will begin and complete as homework. This outline is preliminary and subject to change.


  1. What Are Data? and What Are Good and Bad Depictions of Data?
    • Discussion
      • Visual Display of Quantitative Information, Part I
      • What are data?
      • What is programming? What is R?
      • What is a text editor vs a program?
    • Programming
      • R Graphics Cookbook, Preface, Chapter 1: R Basics, and Chapter 15 (15.1 to 15.7; 15.7): Getting Your Data Into Shape, Chapter 2 (2.1, 2.2)
      • Load R on computer
      • Write “hello world” program
      • Load data
      • Getting ready to graph: calculate means
      • Make a graph or two
    • Supplemental
  2. Visual Perception
    • Discussion
      • What are the key elements of visual perception in graphics?
      • Show Me the Numbers, Chapters 5 (Visual Perception and Graphical Communication) and 7 (General Design for Communication)
    • Programming
      • R Graphics Cookbook, Chapter 2: Graph Basics (2.2-2.6), Chapter 15 Getting Your Data Into Shape (15.7, 15.15-15.17)
      • Load a different dataset than the previous course
      • Make three charts using means
  3. Quantities, Shares and Denominators
    • Discussion
      • Show Me the Numbers, Chapter 6: Fundamental Variations of Graphs
      • Why big numbers matter: McGinty, “Grasping Giant Number is Far From Second Nature”, Wall Street Journal
      • When do you express things as shares?
      • When do you express things in per capita terms?
    • Programming
      • R Graphics Cookbook, Chapter 3: Bar Charts
      • Load a dataset
      • Make a loop
      • Calculate relevant summary statistics
      • Make three charts that show relative quantities
      • One of these charts must be a bar chart
  4. How do you show patterns from individual data points?
    • Discussion
      • Show Me the Numbers, Chapter 10: Component-Level Graph Design
    • Programming
      • R Graphics Cookbook, Chapter 5: Scatter Plots
      • Load a dataset amenable to scatter plots
      • Write a R function
      • Create three scatter plots
  5. Demonstrate Change Over Time
    • Discussion
      • Show Me the Numbers, Chapter 13: Telling Compelling Stories with Numbers
    • Programming
      • R Graphics Cookbook, Chapter 4: Line Graphs
      • Make three charts that show change over time
      • One of these should be a line chart, but they should not all be line charts
  6. How to Best to Show More than One Variable?
    • Discussion
      • Show Me the Numbers, Chapter 11: Displaying Many Variables at Once
    • Programming
      • Make three charts that show the relationship between two different variables
  7. Putting it all Together: An Illustrated Guide to Income in the United States
    • Discussion
      • Mulbrandon, An Illustrated Guide to Income in the United States
      • Chapter 9, “Case Studies”, Storytelling with Data
    • Programming
      • Try to make one or two of these on your own!
  8. Student Consultations
    • March 22 and 23
    • Half-hour discussions of visualizations
  9. In-class Workshop
    • Post your policy brief beforehand
    • Come to class prepared to discuss narrative in brief
    • And to sketch out or improve graphs, including programming
  10. Maps I
  11. Maps II
  12. Maps III
  13. Student Presentations, 1 of 2
    • First half of class: Student Presentations
    • Second half of class: Programming workshop
  14. Student Presentations, 2 of 2
    • First half of class: Student Presentations
    • Second half of class: Programming workshop