Free course

# Introduction to R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

4 Hours62 Exercises2,296,881 Learners6200 XPData Analyst TrackData Scientist TrackR Programming Track

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## Course Description

In this introduction to R course, you'll master the basics of this widely used open source language—including vectors, factors, lists, and data frames. With the coding skills you'll gain in this course, you'll be ready to undertake your own data analysis in R. There are millions of R users worldwide, cementing it as a leading programming language in statistics and data science. More and more organizations are using R, so begin your coding journey in one of DataCamp's most popular courses today!

1. 1

### Intro to basics

Free

Take your first steps with R. In this chapter, you will learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in R. Let's get started.

How it works
100 xp
Arithmetic with R
100 xp
Variable assignment
100 xp
Variable assignment (2)
100 xp
Variable assignment (3)
100 xp
Apples and oranges
100 xp
Basic data types in R
100 xp
What's that data type?
100 xp
2. 2

### Vectors

Free

We take you on a trip to Vegas, where you will learn how to analyze your gambling results using vectors in R. After completing this chapter, you will be able to create vectors in R, name them, select elements from them, and compare different vectors.

3. 3

### Matrices

Free

In this chapter, you will learn how to work with matrices in R. By the end of the chapter, you will be able to create matrices and understand how to do basic computations with them. You will analyze the box office numbers of the Star Wars movies and learn how to use matrices in R. May the force be with you!

4. 4

### Factors

Free

Data often falls into a limited number of categories. For example, human hair color can be categorized as black, brown, blond, red, grey, or white—and perhaps a few more options for people who color their hair. In R, categorical data is stored in factors. Factors are very important in data analysis, so start learning how to create, subset, and compare them now.

5. 5

### Data frames

Free

Most datasets you will be working with will be stored as data frames. By the end of this chapter, you will be able to create a data frame, select interesting parts of a data frame, and order a data frame according to certain variables.

6. 6

### Lists

Free

As opposed to vectors, lists can hold components of different types, just as your to-do lists can contain different categories of tasks. This chapter will teach you how to create, name, and subset these lists.

In the following tracks

Data Analyst Data ScientistR Programming

#### Jonathan Cornelissen

Co-founder of DataCamp

Jonathan Cornelissen is one of the co-founders of DataCamp and the initial DataCamp CEO, and is interested in everything related to data science, education and entrepreneurship. He holds a PhD in financial econometrics, and was the original author of an R package for quantitative finance.