Introduction to R
Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.
- 4 hours
- 0 Videos
- 62 Exercises
- 1,075,418 Participants
- 6,200 XP
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This course is part of these tracks:
Jonathan Cornelissen
Co-founder and CEO of DataCamp
Jonathan Cornelissen is one of the co-founders of DataCamp, and is interested in everything related to data science, R, education and entrepreneurship. He holds a PhD in financial econometrics, and is the author of an R package for quantitative finance. DataCamp is the second education start-up he founded, and the first one that went international. In his spare time, he loves to do some programming, especially in Ruby on Rails.
See MoreCourse Description
In this introduction to R, you will master the basics of this beautiful 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. With over 2 million users worldwide R is rapidly becoming the leading programming language in statistics and data science. Every year, the number of R users grows by 40% and an increasing number of organizations are using it in their day-to-day activities. Leverage the power of R by completing this R online course today!
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1
Intro to basics
In this chapter, you will take your first steps with R. 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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2
Vectors
In this R course, we'll 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.
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3
Matrices
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 to understand how you can do basic computations with them. You will analyze the box office numbers of Star Wars to illustrate the use of matrices in R. May the force be with you!
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4
Factors
Very often, data falls into a limited number of categories. For example, human hair color can be categorized as black/brown/blonde/red/grey/white (and perhaps a few more options for people who dye it). In R, categorical data is stored in factors. Given the importance of these factors in data analysis, you should start learning how to create, subset and compare them now!
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Data frames
Most data sets you will be working with will be stored as data frames. By the end of this chapter focused on R basics, 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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Lists
Lists, as opposed to vectors, can hold components of different types, just like your to-do list at home or at work. This intro to R chapter will teach you how to create, name and subset these lists.
Course Instructor
Jonathan Cornelissen
Co-founder and CEO of DataCamp
Jonathan Cornelissen is one of the co-founders of DataCamp, and is interested in everything related to data science, R, education and entrepreneurship. He holds a PhD in financial econometrics, and is the author of an R package for quantitative finance. DataCamp is the second education start-up he founded, and the first one that went international. In his spare time, he loves to do some programming, especially in Ruby on Rails.
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