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Introduction to R

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

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4 Hours62 Exercises2,092,668 Learners
6200 XP

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Course Description

In Introduction to R, you will master the basics of this widely used open source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science. Every year, the number of R users grows by about 40%, and an increasing number of organizations are using it in their day-to-day activities. Begin your journey to learn R with us 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.

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    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. 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!

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  3. 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.

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  4. 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.

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  5. 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.

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In the following tracks

Data Analyst Data ScientistR Programming
Jonathan Cornelissen Headshot

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.

More information at: jonathancornelissen.com
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What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA