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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.
In this introduction to R, you will master the basics of this beautiful open source language such as factors, lists and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.
Intro to basicsFree
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!Meet R50 xpYour first R script100 xpDocumenting your code100 xpR as a calculator100 xpR's pros and cons50 xpVariable assignment (1)100 xpVariable assignment (2)100 xpVariable assignment (3)100 xpThe workspace100 xpBasic Data Types50 xpDiscover Basic Data Types100 xpBack to Apples and Oranges100 xpWhat's that data type?50 xpCoercion: Taming your data100 xp
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.Create and Name Vectors50 xpCreate a vector (1)100 xpCreate a vector (2)100 xpNaming a vector (1)100 xpNaming a vector (2)100 xpVector Arithmetic50 xpCalculate your earnings100 xpCalculate total winnings: sum()100 xpVector Subsetting50 xpSelection by index (1)100 xpSelection by index (2)100 xpSelection by name100 xpSelection by logicals (1)100 xpSelection by logicals (2)100 xp
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!Create and Name Matrices50 xpAnalyzing matrices, you shall (1)100 xpAnalyzing matrices, you shall (2)100 xpNaming a matrix100 xpCalculating the worldwide box office100 xpAdding a row100 xpThe total box office revenue for the entire saga100 xpSubsetting Matrices50 xpSelect elements100 xpSelect rows and columns100 xpCreate submatrices100 xpAlternative ways of subsetting100 xpMatrix Arithmetic50 xpArithmetic with matrices (1)100 xpArithmetic with matrices (2)100 xp
Very often, data falls into a limited number of categories.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!
Lists, as opposed to vectors, can hold components of different types, just like your to-do list at home or at work. This chapter will teach you how to create, name and subset these lists!
Most data sets you will be working with will be stored as a data frame. 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.Explore the Data Frame50 xpHave a look at your data set100 xpHave a look at the structure100 xpCreating a data frame (1)100 xpCreating a data frame (2)100 xpRename the data frame columns100 xpSubset, Extend & Sort Data Frames50 xpSelection of data frame elements100 xpOnly planets with rings (1)100 xpOnly planets with rings (2)100 xpOnly planets with rings but shorter100 xpAdd variable/column100 xpSorting100 xpSorting your data frame100 xp
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.
Harvard Business School
DataCamp is by far my favorite website to learn from.
Decision Science Analytics, USAA