Garrett is the author of Hands-On Programming with R and R for Data Science from O'Reilly Media. He is a Data Scientist at RStudio and holds a Ph.D. in Statistics, but specializes in teaching. He's taught people how to use R at over 50 government agencies, small businesses, and multi-billion dollar global companies; and he's designed RStudio's training materials for R, Shiny, dplyr and more and is a frequent contributor to the RStudio blog. He wrote the popular lubridate package for R.
In the first part of this two-part RStudio tutorial, you will learn how to use RStudio, an IDE for R.
Chapter 1 will cover:
Chapter 2 will get into the features of the IDE geared toward making you a more effective R programmer, including code diagnostics and running scripts.
Finally, Part 1 finishes with a brief chapter on using RStudio projects for organizing and sharing your code with others.
In Part 2, you will learn how RStudio makes it easy to build your own R packages, integrate with GitHub, and use tools like R Markdown.
This chapter shows you around the most important parts of the RStudio IDE. You'll learn about the data viewer, the environment tab, the history tab, how to set and get your working directory, using the plots pane, navigating the help tab when you get stuck, and more.
This chapter builds on the last by showing you how to take advantage of the IDE for a more efficient and enjoyable R programming experience. For example, you'll see how RStudio's built-in code and style diagnostics can flag things before they go terribly wrong. You'll learn tricks for using multiple cursors at once, collapsing code for better visibility, and using RStudio's handy tools for debugging your code.
In this brief chapter, you'll see how to use RStudio projects to organize and share your code with others. Projects come with many benefits, including the ability to keep all relevant files in one place and to easily search all of these files with a single command. You'll also be exposed to the Packrat system for package management and reproducibility.