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Introduction to R

220 reviews

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

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4 Hours62 Exercises2,434,043 Learners6200 XPData Analyst with R TrackData Scientist with R TrackR Programming Track

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Course Description

Learn R Programming

R is the most popular programming language in the data industry thanks to its use of vectors and its variety of pre-processed packages. It’s in high demand for Data Scientists, Analysts, and Statisticians alike and is capable of handling AI, machine learning, financial analysis, and much more.

This introduction to R course covers the basics of this open source language, including vectors, factors, lists, and data frames. You’ll gain useful coding skills and be ready to start your own data analysis in R.

Gain an Introduction to R

You’ll get started with basic operations, like using the console as a calculator and understanding basic data types in R. Once you’ve had a chance to practice, you’ll move on to creating vectors and try out your new R skills on a data set based on betting in Las Vegas.

Next, you’ll learn how to work with matrices in R, learning how to create them, and perform calculations with them. You’ll also examine how R uses factors to store categorical data. Finally, you’ll explore how to work with R data frames and lists.

Master the R Basics for Data Analysis

By the time you’ve completed our Introduction to R course, you’ll be able to use R for your own data analysis. These sought-after skills can help you progress in your career and set you up for further learning. This course is part of several tracks, including Data Analyst with R, Data Scientist with R, and R Programming, all of which can help you develop your knowledge.
  1. 1

    Intro to basics


    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



    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



    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


    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



    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 with RData Scientist with RR 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.

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Don’t just take our word for it

from 220 reviews
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  • Lingjia S.
    about 6 hours

    basic knowledge, great operate interface

  • Nadina D.
    about 16 hours


    about 16 hours

    Really good

  • lawrence a.
    about 16 hours

    it has played a great role in exposing me to R

  • Josue M.
    1 day

    Es un curso muy bien estructurado que te enseña paso a paso.

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"basic knowledge, great operate interface"

Lingjia S.


Nadina D.

"Really good"


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