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)

Required Packages

In this appendix, I will show you how to install the software you need to replicate the examples shown in this book. I will show you how to do so for Linux and macOS, specifically, Ubuntu 17.10 and High Sierra. If you're using Windows, the same principles apply but the specifics may be a bit different. However, I'm sure it will not be too difficult in any case.

There are two types of requirements for executing all the code in this book: external and internal. Software outside of R, is what I call external requirements. Software inside of R, meaning R packages, are what I refer to as internal requirements. I will walk you through the installation of both of these.