Book Image

Learning R Programming

By : Kun Ren
Book Image

Learning R Programming

By: Kun Ren

Overview of this book

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.
Table of Contents (21 chapters)
Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Functions


A function is an object you can call. Basically, it is a machine with internal logic that takes a group of inputs (parameters or arguments) and returns a value as output.

In the previous sections, we encountered some built-in functions of R. For example, is.numeric() takes an argument that can be any R object and returns a logical value that indicates whether the object is a numeric vector. Similarly, is.function() can tell whether a given R object is a function object.

In fact, in R environment, everything we use is an object, everything we do is a function, and, maybe to your surprise, all functions are still objects. Even <- and + are both functions that take two arguments. Although they are called binary operators, they are essentially functions.

When we do casual, interactive data analysis, at times, we won't have to write any function on our own since the built-in functions and those provided by thousands of packages are usually enough.

However, if you need to repeat your...