2 Data structures

Contrast how you see a fish and how computers see fish. Our job is to bridge the gap. No problem…

In this chapter, we will introduce basic data structures and how to work with them in R. One of our challenges is to understand how R sees our data.

R is what is known as a “high-level” or “interpreted” programming language, in addition to being “functional” and “object-oriented”. This means the pieces that make it up are a little more intuitive to the average user than most low-level languages like C or C++. The back-end of R is, in fact, a collection of low-level code that builds up the functionality that we need. This means that R has a broad range of uses, from data management to math, and even GIS and data visualization tools, all of which are conveniently wrapped in an “intuitive”, “user-friendly” language.

Part of this flexibility comes from the fact that R is also a “vectorized” language. Holy cow, R is so many things. But, why do you care about this? This will help you wrap your head around how objects are created and stored in R, which will help you understand how to make, access, modify, and combine the data that you will need for any approach to data analysis. It is maybe easiest to see by taking a look at some of the data structures that we’ll work with.

We will work exclusively with objects and functions created in base R for this Chapter, so you do not need any of the class data sets to play along.