As you work through the book, I will teach you not just how to program with R, but how to use the programming skills to support your work as a data scientist. When you work with data, you will need to store, retrieve, and manipulate large sets of values without introducing errors. The projects will also teach you how to write vectorized R code, a style of lightning-fast code that takes advantage of all of the things R does best.īut, more importantly, the projects will teach you how to solve the logistical problems of data science-and there are many logistical problems. You will learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools, such as if else statements, for loops, S3 classes, R’s package system, and R’s debugging tools. First, they cover the breadth of the R language.
The chapters in the book are arranged according to three practical projects–given that they’re fairly substantial projects, they span multiple chapters.
I want to help you become a data scientist, as well as a computer scientist, so this book will focus on the programming skills that are most related to data science. But this is not a typical introduction to R. You’ll go from loading data to writing your own functions (which will outperform the functions of other R users). This book will teach you how to program in R.
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