3.5 Conclusion
3.5.1 Summary
The previous and this chapter provided a very brief introduction to R (R Core Team, 2021b). Conceptually, we introduced and distinguished between
- different types of R objects (e.g., data vs. functions),
- different types of data (e.g., logical, numeric, and character data), and
- different data structures and shapes of data (e.g., linear vs. rectangular vectors or lists).
In R, a range of different objects are created and changed by applying functions (e.g., for assignment, arithmetic, and many other operations). Thus, the following chapters gravitate around creating more objects and using a large variety of functions to do things with them.
3.5.2 Resources
There is no shortage of introductory books and scripts on R, but it is helpful to look for one that fits your interests and level of expertise.
Books and online scripts
As most introductions of R focus on vectors and data frames, they provide only scarce information on other data structures. Some noteworthy exceptions (with dedicated chapters or sections on lists and factors) are:
Norman Matloff’s The art of R programming (Matloff, 2011)
Hadley Wicham’s and Garrett Grolemund’s textbook R for Data Science (r4ds) (Wickham & Grolemund, 2017)
Hadley Wickham’s books on Advanced R (1st and 2nd edition) (Wickham, 2014a, 2019a)
Cheatsheets
Here are some pointers to related RStudio cheatsheets:
- Base R:
Figure 3.1: Base R summary from RStudio cheatsheets.
- Advanced R:
Figure 3.2: (ref:fig-struc-cheat-adva-R1)
Miscellaneous
Other helpful links that do not fit into the above categories include:
R-bloggers collects blog posts on R.
R-exercises provides categorized sets of exercises to help people developing their R programming skills.
Quick-R (by Robert Kabacoff) is a popular website on R programming.
3.5.3 Preview
In Chapter 4, we will learn to use R functions for visualizing data.