Book Image

R Programming By Example

By : Omar Trejo Navarro
Book Image

R Programming By Example

By: Omar Trejo Navarro

Overview of this book

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.
Table of Contents (12 chapters)

Summary

In this chapter, we have introduced the fundamentals behind object-oriented programming, and we have seen how to implement object-oriented systems within R with three different object models: S3, S4, and R6. We looked at the fundamental building blocks of object models, such as encapsulation, polymorphism, and hierarchies. We have shown you how to implement parametric polymorphism with S3 and S4, as well as regular polymorphism with R6, and we have shown how to use concepts like interfaces, even when there's no explicit support for them in R.

We have implemented a full object-oriented system to track cryptocurrencies information, and, while doing so, have looked at various patterns and techniques, as well as how the three different object models can be used together.

The type of object model to use is the subject of some controversy among R programmers, and the decision...