R for Data Science

Part II. Wrangle

In this part of the book, you’ll learn about data wrangling, the art of getting your data into R in a useful form for visualization and modeling. Data wrangling is very important: without it you can’t work with your own data! There are three main parts to data wrangling:

This part of the book proceeds as follows:

• In Chapter 7, you’ll learn about the variant of the data frame that we use in this book: the tibble. You’ll learn what makes them different from regular data frames, and how you can construct them “by hand.”

• In Chapter 8, you’ll learn how to get your data from disk and into R. We’ll focus on plain-text rectangular formats, but will give you pointers to packages that help with other types of data.

• In Chapter 9, you’ll learn about tidy data, a consistent way of storing your data that makes transformation, visualization, and modeling easier. You’ll learn the underlying principles, and how to get your data into a tidy form.

Data wrangling also encompasses data transformation, which you’ve already learned a little about. Now we’ll focus on new skills for three specific types of data you will frequently encounter in practice:

• Chapter 10 will give you tools for working with multiple interrelated datasets.

• Chapter 11 will introduce regular expressions, a powerful tool for manipulating strings.

• Chapter 12 will show ...