The following two videos are helpful to understand why we should learn R.
Why Data Scientists Use R? Reasons to learn the R Programming Language
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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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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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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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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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, 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.
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