Chapter 3 Making Graphs

3.1 Class material

Note: most of this class talk in workshop style, so any recordings are short and the slides are brief

We will work through these files as in-class exercises: class3a.R and class3b.R. These are based on Healy (2018) chapters 2 and 3 respectively.

Reading the first 3 chapters of Healy (2018) before the next class is essential

3.2 Resources

This book is recommended for the course, and for this lecture in particular:

Healy, K. (2018). Data visualization: a practical introduction. Princeton University Press.

• The whole book is available online via the link
  
• There are supporting materials here: https://github.com/kjhealy/socviz

3.2.1 Other resources

• We are going to be using the ggplot package for our visualisations: ggplot2
• Five Charts You’ve Never Used but Should
• guru99: Scatter Plot in R using ggplot2 (with Example)
• ggplot2: Elegant Graphics for Data Analysis, the chapter on Themes
• Giulia Ruggeri, Better data communication with {ggplot2}Styling a chart and improving the text using {forcats} and {ggtext} and {scales}, Better data communication with {ggplot2}, part 2
• datanovia.com: GGPlot Axis Ticks: Set and Rotate Text Labels
• anthonyhobday.com: [Visual design rules you can safely follow every time][https://anthonyhobday.com/sideprojects/saferules)

3.3 Post-class exercises

Review the introduction and Chapter 1 ‘Look At Data’ of Healy (2018)

Work through Chapter 2 ‘Get Started’ from 2.3 onwards (“Things to know about R”), we are ignoring the material on RMarkdown for now (we’ll get there, see here).

Work through Chapter 3 ‘Make a plot’

3.4 Checklist

Worked through the scripts linked at the top of this page

Completed the post reading from Healy (2018)

• especially section 3.8 ‘Where to go next’ in Chapter 3 ‘Make a plot’

Key concepts (chapter 2):

• variables and functions
• variables are typed (e.g. can be numeric or character)
• and how you detect what type a variable is
• indexing for variables and data frames

In the console, understood

• the shortcut keys for the assignment operator <-
• the use of tab for autocomplete
• the use up arrow to cycle through previous commands
• CTRL + ENTER to run highlighted text

Key concepts (chapter 3):

• Tidydata
  • long vs wide data
  • values and keys
  • data variables can be continuous or factors
• The fundamental ggplot “recipe”
  • plots have data, aesthetic mappings (‘aes’, ‘mappings’) and layers
  • adding mappings, adding geoms, geom properties, other layers (e.g. labs)
  • mappings are inherited by geom layers