02. Data Viz

Examples, good and bad. Theory underlying what makes a viz good and bad. Tools to implement viz tasks.

Artwork by @allison_horst.

Agenda

August 28, 2024

1. GitHub
2. NSSD
3. Grammar of graphics
4. ggplot

September 4, 2024

1. Cholera: what went (didn’t go) well with the graphics?
2. Challenger: what didn’t go (went) well with the graphics?
3. Thoughts on plotting (with example(s))

• Class discussion will be based on Tufte (1997) Visual and Statistical Thinking: Displays of Evidence for Making Decisions. (Use Google to find it.)

• Another great reference is the following text: Fundamentals of Data Visualization by Wilke at http://serialmentor.com/dataviz/

Readings

• Class notes: Visualization

• Tufte (1997) Visual and Statistical Thinking: Displays of Evidence for Making Decisions. (Use Google to find it.)

• Wickham (2017) Data Visualization in R for Data Science.

Reflection questions

• When creating a graph, try to sketch / image the graph before you code it. What do you want R to do (what is the goal)? In order to do that, what does R need to know?

• What should the goal of a plot be? What should the goal of your plot be?

• What different aspects deconstruct a plot?

Ethics considerations

• Does your plot make the comparison of interest: easily? and accurately?

• Did you add alt text to your images (see Writing Alt Text for Data Visualization)?

• Is your plot accessible to those who are color blind or looking at the image in black and white?

Slides

• In class slides for both 8/28/24 and 9/4/24.

• WS3 - ggplot

Additional Resources

• DuBois’s images online and in W.E.B. Du Bois’s Data Portraits: Visualizing Black America, a compilation edited by Whitney Battle-Baptiste.
• Flowcharts for choosing appropriate plots, brief tutorials of viz types, and source code in R and Python: from Data to Viz
• See something or Say Something
• Census trends visualized
• Visualization Internship (Fall 2021) at 538
• visualizing data: Digest of the best visualizations from the past month
• A regular NYT column on visualizations: What’s Going on in this Graph?
• Studies about visualizations and perception
• Fundamentals of Data Visualization
• Allison Horst’s amazing illustrations
• Makeover Mondays, a weekly data project for making more effective visualizations.

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