Overview

In your first mini-project, you’ll apply what you’ve learned about ggplot2 and design principles to replicate and redesign a published graph. This project consists of three parts:

  1. Replicating an existing graph using ggplot2. Depending on the graph you choose, this may require some creativity in recreating data.
  2. Glow-up: Using design principles from class, re-design the original graph to be better. This should include, at minimum, a change of geom and color/font choices.
  3. Glow-down: Using design principles from class, re-design the original graph to be as bad as you can, while still being technically correct.
  4. A 1-page written summary including (1) an evaluation of the original graph, (2) reasoning for your design choices in improving the graph, (3) a short description of why your glow-down is worse than the original graph. This should include references to readings and discussions from class.

Options and Examples

  • FiveThirtyEight + Associated R Package (See available data here). I want to acknowledge that FiveThirtyEight has a white supremacy problem, as does much of the journalism + data world. Farai Chideya and Mona Chalabi, two former employees, have both spoken out about the traumatizing culture during their time there. The R Package linked here is maintained by folks outside of fivethirtyeight and the company does not profit in any way from us using their data. I’m a little uncomfortable using it as a source in this class, but fivethirtyeight has become so pervasive in the data analysis and visualization world that I’ve decided to include it.
  • HelpMeViz
  • DataIsPlural
  • TidyTuesday – If you choose this option, please be especially kind in your critique. This is a weekly R community activity, and many submissions are by beginners.

You do not have to choose a graph from one of these sources. It can be hard to find associated data with some published graphs, so don’t spend too much time trying to find data for a specific graph before moving on.

Submission

Your submission should include three visualizations (replication, improvement, de-improvement), a written overview of your work, and all associated code. I strongly recommend working in an rmarkdown document, knitting to PDF, and attaching your .Rmd and data files as supplementary material.

Rubric

A satisfactory project will:

  • Use a dataset/visualization not discussed in class
  • Include all necessary code for recreation
  • Be well-written and thoughtful
  • Meet minimum submission quality (no typos, appropriate labels and font sizes, a readable theme)

An excellent project will meet all of the requirements for a satisfactory project, plus one of:

  • An ambitious dataset or visualization choice
  • An especially creative improvement or un-improvement (eg non-obvious geom choices, transformation of the underlying data, or using ggplot2 customizations we haven’t done in class yet)
  • Be publication-ready/especially polished.

Please include a self-grade (with explanation) at the end of your report.