Week 4: Visualisation

This week provides an introduction to the core principles of visualisation, and then demonstrates how to create visualisations and maps using the {ggplot2} package in R.

Lecture Slides   Supporting Code  

Note: materials will be posted before lecture and seminar each week.

Additional resources

• Wickham, Hadley, Mine �etinkaya-Rundel and Garett Grolemund. 2023. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 2nd ed. Sebastopol, CA: O’Reilly. Chs. 1, 9, 10 and 11. Available at https://r4ds.hadley.nz/.

• {ggplot2} docs

• Wickham, Hadley, Danielle Navarro, and Thomas Lin Pedersen. ggplot2: Elegant Graphics for Data Analysis. 3rd ed. Available at https://ggplot2-book.org/.

• R Graph Gallery. “ggplot2.” Available at https://www.r-graph-gallery.com/ggplot2-package.html.

• Two recent video workshops by Thomas Lin Pedersen, video 1, video 2, and the repo with associated exercises

• Healy, Kieran. 2019. Data Visualization: A Practical Introduction. Princeton, NJ: Princeton University Press, ch. 1. Book available at https://socviz.co/.

• Tufte, Edward. 2001. The Visual Display of Quantitative Information. 2nd ed. Information available at https://www.edwardtufte.com/tufte/books_vdqi.

• Wilkinson, Leland. 2005. The Grammar of Graphics. 2nd ed. New York: Springer, 2005. Ch. 1. E-book available from the LSE Library at https://librarysearch.lse.ac.uk/permalink/44LSE_INST/1f110cn/alma99128824410302021.