Data science is a popular buzzword in the information technology industry. It is very much essential to running a successful business, that is, for analyzing the huge amounts of business and customer data. Hence, all industries now use data science concepts to improve their brands. R, an open-source tool, has a lot of functions for statistical computing. Therefore, the R program is the natural choice for data science applications.

This book covers various application programming interfaces (APIs), libraries, and packages that can be used for R data science applications. Its 13 short chapters cover dozens of R functions. The book does not directly present functions in R; instead it covers the application of R to data science using the tidyverse package, that is, a set of functions and packages in R that are highly customized for data science applications.

The tidyverse functions and packages covered in this book include readr, tibble, tidyr, magrittr, purr, dplyr, stringr, forcats, lubridate, modelr, and ggplot2. All of the syntax is clearly presented and illustrated with examples.

This book basically looks at data science applications when data is represented in tabular form. It presents how to import, represent, and reformat data. In addition, it covers how to work with strings, factors, dates, and models. Manipulating and plotting data are also explained.

This book is easy to read. However, the title should have included tidyverse so that readers know what to expect. It will be useful for undergraduate students and beginners in data science.