Data structures

Data stuctures

Vectors

The basic data structure in R is the vector, which comes in two basic flavours: atomic vectors and lists. Atomic vectors can be logical, integer, numeric, or character, or less commonly complex or raw.

Vectors have three properties: mode, length and names:

x <- 1:10
mode(x)
length(x)
names(x)

names(x) <- letters[1:10]
x
names(x)

Lists

Lists are different from atomic vectors in that they can contain any other type of vector. This makes them recursive, because a list can contain other lists.

x <- list(list(list(list())))
x
str(x)

str is one of the most important functions in R: it gives a human readable description of any R data structure.

Matrices and arrays

Vectors can be extended into multiple dimensions. If 2d they are called matrices, if more than 2d they are called arrays. Length generalises to nrow and ncol for matrices, and dim for arrays. Names generalises to rownames and colnames for matrices, and dimnames for arrays.

y <- matrix(1:20, nrow = 4, ncol = 5)
z <- array(1:24, dim = c(3, 4, 5))

nrow(y)
rownames(y)
ncol(y)
colnames(y)

dim(z)
dimnames(z)

All vectors can also have additional arbitrary attributes - these can be thought of as a named list (although the names must be unique), and can be accessed individual with attr or all at once with attributes. structure returns a new object with modified attributes.

Data frames

Another extremely important data structure is the data.frame. A data frame is a named list with a restriction that all elements must be vectors of the same length. Each element in the list represents a column, which means that each column must be one type, but a row may contain values of different types.

Attributes

You can think of attributes as a named set that can be attached to any R object.

• classs
• dim, dimnames
• names

The class attribute is used to implement S3.

attributes, attr, attr<-