Factors form the basis for many of R’s powerful operations, including many of those performed on tabular data. The motivation for factors comes from the notion of nominal, or categorical, variables in statistics. These values are nonnumerical in nature, corresponding to categories such as Democrat, Republican, and Unaffiliated, although they may be coded using numbers.
In this chapter, we’ll begin by looking at the extra information contained in factors and then focus on the functions used with factors. We’ll also explore tables and common table operations.
An R factor might be viewed simply as a vector with a bit more information added (though, as seen below, it’s different from this internally). That extra information consists of a record of the distinct values in that vector, called levels. Here’s an example:
> x <- c(5,12,13,12) > xf <- factor(x) > xf [1] 5 12 13 12 Levels: 5 12 13
The distinct values in xf—5, 12, and 13—are the levels here.
Let’s take a look inside:
> str(xf) Factor w/ 3 levels "5","12","13": 1 2 3 2 > unclass(xf) [1] 1 2 3 2 attr(,"levels") [1] "5" "12" "13"
This is revealing. The core of xf here is not (5,12,13,12) but rather (1,2,3,2). The latter means that our data consists first of a level-1 value, then level-2 and level-3 values, and finally another level-2 value. So the data has been recoded by level. The levels themselves are recorded too, of course, though as characters such as "5" rather than 5.
The length of a factor is still defined in terms of the length of the data rather than, say, being a count of the number of levels:
> length(xf) [1] 4
We can anticipate future new levels, as seen here:
> x <- c(5,12,13,12) > xff <- factor(x,levels=c(5,12,13,88)) > xff [1] 5 12 13 12 Levels: 5 12 13 88 > xff[2] <- 88 > xff [1] 5 88 13 12 Levels: 5 12 13 88
Originally, xff did not contain the value 88, but in defining it, we allowed for that future possibility. Later, we did indeed add the value.
By the same token, you cannot sneak in an “illegal” level. Here’s what happens when you try:
> xff[2] <- 28 Warning message: In `[<-.factor`(`*tmp*`, 2, value = 28) : invalid factor level, NAs generated