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 introduced the book by mentioning its intended audience, as well as our intentions for it, which are to provide examples that you can use to understand how real-world R applications are built using a high-quality code, and the useful guidelines of what to do and not to do when building your own applications.

We also introduced R's basic constructs and prepared the baseline we need to work through the examples developed in the rest of the book. Specifically, we looked at how to work with the console, how to create and use variables, how to work with R basic data types like numerics, characters, and logicals, as well as how to handle special values, and how to make basic use of data structures like vectors, factors, matrices, data frames, and lists. Finally, we showed how to create our own functions and how to provide multiple paths of execution with control structures.

I hope this book is useful to you and that you enjoy reading it.