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

Summary


In this chapter, you learned the basic concepts of object-oriented programming: class and methods and how they are connected by generic functions in R through method dispatch. You learned how to create S3, S4, RC, and R6 classes and methods. These systems share similar ideas but are distinct in implementation and usage. Hadley Wickham gives some nice suggestions in picking a system (http://adv-r.had.co.nz/OO-essentials.html#picking-a-system).

After getting familiar with R's most important features, we will discuss more practical topics in the subsequent chapters. In the next chapter, you will learn about the packages and techniques used to access popular databases. You will gain necessary knowledge and techniques to connect R to relational databases such as SQLite and MySQL as well as the upcoming non-relational databases such as MongoDB and Redis.