R for Data Science, 2nd Edition

Introduction

Data science is an exciting discipline that allows you to transform raw data into understanding, insight, and knowledge. The goals of R for Data Science are to help you learn the most important tools in R that will allow you to do data science efficiently and reproducibly and to have some fun along the way! After reading this book, you’ll have the tools to tackle a wide variety of data science challenges using the best parts of R.

Preface to the Second Edition

Welcome to the second edition of R for Data Science (R4DS)! This is a major reworking of the first edition, removing material we no longer think is useful, adding material we wish we included in the first edition, and generally updating the text and code to reflect changes in best practices. We’re also very excited to welcome a new co-author: Mine Çetinkaya-Rundel, a noted data science educator and one of our colleagues at Posit (the company formerly known as RStudio).

A brief summary of the biggest changes follows:

• The first part of the book has been renamed to “Whole Game.” The goal of this section is to give you the rough details of the “whole game” of data science before we dive into the details.

• The second part of the book is “Visualize.” This part gives data visualization tools and best practices a more thorough coverage compared to the first edition. The best place to get all the details is still the ggplot2 book, but now R4DS covers more of the most important techniques.

• The third part of the ...