Whole game

Our goal in this part of the book is to give you a rapid overview of the main tools of data science: importing, tidying, transforming, and visualizing data, as shown in Figure 1. We want to show you the “whole game” of data science giving you just enough of all the major pieces so that you can tackle real, if simple, datasets. The later parts of the book will hit each of these topics in more depth, increasing the range of data science challenges that you can tackle.

A diagram displaying the data science cycle: Import -> Tidy -> Understand  (which has the phases Transform -> Visualize -> Model in a cycle) -> Communicate. Surrounding all of these is Program Import, Tidy, Transform, and Visualize is highlighted.
Figure 1: In this section of the book, you’ll learn how to import, tidy, transform, and visualize data.

Four chapters focus on the tools of data science:

Nestled among these chapters are four other chapters that focus on your R workflow. In 2  Workflow: basics, 4  Workflow: code style, and 6  Workflow: scripts and projects you’ll learn good workflow practices for writing and organizing your R code. These will set you up for success in the long run, as they’ll give you the tools to stay organized when you tackle real projects. Finally, 8  Workflow: getting help will teach you how to get help and keep learning.