14  Our World in Data Part 1

Readings

Chapter 11 Communication: R for Data Science (2nd ed)

Creating custom, stylized ggplot2 themes can get complicated very quickly. Finding answers and examples on Google is easier if you know what key words to search for. These reference sheets/pages helpful as you learn the ggplot lingo..

Guided Instruction

Visualization for Presentation

The Our World in Data website publishes research and graphics that provide insight into world data. We are going to recreate one of their charts and use it to practice our annotation skills.

If the thing you want to edit is not a theme element, then it is related to data and can mostly likely be changed inside a geom_() or a scale_() layer.

  1. Recreate this graph as closely as you can. This will/should take the bulk of your time.
    • The data is provided on the download tab.
    • Focus your energy on the y-axis, axes, legend, lines, scales, etc. Pay attention to detail.
      • Notice the x-axis is log transformed.
    • Do NOT worry about making your graph interactive. Ignore that aspect completely
    • For now, don’t worry about labeling the countries on the plot. We’ll do some labeling below.
    • If you are getting stuck matching the graph exactly, try completing steps 2 and 3, then coming back to this step with the time you have left.
  2. Create a graph that highlights (draws attention to) 3 or 4 specific countries you are interested in. Be creative.
  3. Create another graph that highlights/emphasizes points all from the same continent.
  4. Write a paragraph summarizing insights you gained, or new skills/commands you learned in this task. Also reflect on how you can use “highlighting” to help the data tell a story.
  5. Render the .qmd file. Push all files created as part of the render to your GitHub repository.

Submit

In I-learn submit a link to the .md file on GitHub.