A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R

Chapter 2R Data, Part 1: Vectors

The basic unit of computation in R is the vector. A vector is a set of one or more basic objects of the same kind. (Actually, it is even possible to have a vector with no objects in it, as we will see, and this happens sometimes.) Each of the entries in a vector is called an element. In this chapter, we talk about the different sorts of vectors that you can have in R. Then, we describe the very important topic of subsetting, which is our word for extracting pieces of vectors – all of the elements that are greater than 10, for example. That topic goes together with assigning, or replacing, certain elements of a vector. We describe the way missing values are handled in R; this topic arises in almost every data cleaning problem. The rest of the chapter gives some tools that are useful when handling vectors.

2.1 Vectors

By a “basic” object, we mean an object of one of R's so-called “atomic” classes. These classes, which you can find in help(vector), are logical (values TRUE or FALSE, although T and F are provided as synonyms); integer; numeric (also called double); character, which refers to text; raw, which can hold binary data; and complex. Some of these, such as complex, probably won't arise in data cleaning.

2.1.1 Creating Vectors

We are mostly concerned with vectors that have been given to us as data. However, there are a number of situations when you will need to construct your own vectors. Of course, since a scalar is a vector of length ...