You can get pretty far in R just using vectors. That’s what Chapter 2 is all about. This chapter moves beyond vectors to recipes for matrices, lists, factors, and data frames. If you have preconceptions about data structures, I suggest you put them aside. R does data structures differently.
If you want to study the technical aspects of R’s data structures, I suggest reading R in a Nutshell (O’Reilly) and the R Language Definition. My notes here are more informal. These are things I wish I’d known when I started using R.
Here are some key properties of vectors:
All elements of a vector must have the same type or, in R terminology, the same mode.
v refers to the second element of
v[c(2,3)] is a subvector of
v that consists of the second and third
Vectors have a
names property, the same
length as the vector itself, that gives names to the
v <- c(10, 20, 30)>
names(v) <- c("Moe", "Larry", "Curly")>
print(v)Moe Larry Curly 10 20 30
Continuing the previous example:
Lists can contain elements of different types; in R terminology, list elements may have different modes. Lists can even contain other structured objects, such as lists and data frames; this ...