2.8 Resources

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

2.8.1 Help on visualization

In addition to Chapter 3: Data visualization, Chapter 7: Exploratory data analysis (EDA) (to be covered in 2 weeks) provides further information on data visualization.

The following links provide additional information on using ggplot2:

Data visualization with ggplot2 summary from RStudio cheatsheets.

Figure 2.8: Data visualization with ggplot2 summary from RStudio cheatsheets.

Books or scripts on data visualization include:

The landmark publications by Jacques Bertin (e.g., Bertin, 2011) and Edward R. Tufte (Tufte, 2001, 2006; Tufte, Goeler, & Benson, 1990) provide solid advice and many inspiring examples.

More recent publications that are geared to the needs of aspiring data scientists include:

More specific resources on the principles of data visualization (with many beautiful or bizarre examples) include:

Inspiration and tools for additional types of visualizations can be found at (from specific to general):

2.8.2 Colors in R

The grDevices component of R comes with many options and tools for selecting and modifying colors:

  • Call colors() or demo("colors") in the Console to view the in-built colors of R.

See Appendix D for a primer on using colors in R and Section D.7 for corresponding resources and links.

2.8.3 Explanation: Same stats, different data

The introductory data examined above (in Section 2.1 and plotted in Figure 2.2) is known as Anscombe’s quartet (Anscombe, 1973) and is included in R as anscombe in the datasets package (R Core Team, 2021). It contains four sets of x-y coordinates which have the same statistical properties (regarding mean, SD, correlation, regression line), yet are actually quite different. (See ?anscombe for details.)

Related web links include:


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[02_visualize.Rmd updated on 2021-06-15 15:18:55 by hn.]