2.8 Resources

As they help us to make sense of data, visualizations appear in most chapters of this book (e.g., Chapter 4 on Exploring data). Similarly, the r4ds textbook by Wickham & Grolemund (2017) introduces visualizations in Chapter 3: Data visualization and provides further information and examples in Chapter 7: Exploratory data analysis (EDA).

This section contains links to general resources on visualization and to the ggplot2 package.


Anscombe, F. J. (1973). Graphs in statistical analysis. The American Statistician, 27(1), 17–21. https://doi.org/10.2307/2682899
Bertin, J. (2011). Semiology of graphics: Diagrams, networks, maps (Vol. 1). ESRI Press.
Cairo, A. (2012). The functional art: An introduction to information graphics and visualization. Berkeley CA: New Riders.
Cairo, A. (2016). The truthful art: Data, charts, and maps for communication. Berkeley CA: New Riders.
Chang, W. (2012). R graphics cookbook: Practical recipes for visualizing data (2nd ed.). Retrieved from https://r-graphics.org/
Cleveland, W. S., & McGill, R. (1985). Graphical perception and graphical methods for analyzing scientific data. Science, 229(4716), 828–833. https://doi.org/10.1126/science.229.4716.828
Healy, K. (2018). Data visualization: A practical introduction. Retrieved from https://socviz.co/
Kabacoff, R. (2018). Data visualization with R. Retrieved from https://rkabacoff.github.io/datavis/
Locke, S., & D’Agostino McGowan, L. (2018). datasauRus: Datasets from the datasaurus dozen. Retrieved from https://CRAN.R-project.org/package=datasauRus
Matejka, J., & Fitzmaurice, G. (2017). Same stats, different graphs: Generating datasets with varied appearance and identical statistics through simulated annealing. Proceedings of the 2017 CHI conference on human factors in computing systems, 1290–1294. https://doi.org/10.1145/3025453.3025912
R Core Team. (2021). R base: A language and environment for statistical computing. Retrieved from https://www.R-project.org
Tufte, E. R. (2001). The visual display of quantitative information (2nd ed.). Cheshire, CT: Graphics Press.
Tufte, E. R. (2006). Beautiful evidence (Vol. 1). Cheshire, CT: Graphics Press.
Tufte, E. R., Goeler, N. H., & Benson, R. (1990). Envisioning information (Vol. 126). Cheshire, CT: Graphics Press.
Wickham, H. (2016). ggplot2: Elegant graphics for data analysis (2nd ed.). Retrieved from https://ggplot2-book.org/
Wickham, H., Chang, W., Henry, L., Pedersen, T. L., Takahashi, K., Wilke, C., … Dunnington, D. (2021). ggplot2: Create elegant data visualisations using the grammar of graphics. Retrieved from https://CRAN.R-project.org/package=ggplot2
Wickham, H., & Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. Retrieved from http://r4ds.had.co.nz
Wilke, C. O. (2019). Fundamentals of data visualization: A primer on making informative and compelling figures. Retrieved from https://clauswilke.com/dataviz/
Wilkinson, L. (2005). The grammar of graphics (2nd edition). Springer.
Yau, N. (2011). Visualize this: The FlowingData guide to design, visualization, and statistics. Hoboken, NJ: John Wiley & Sons.
Yau, N. (2013). Data points: Visualization that means something. Hoboken, NJ: John Wiley & Sons.