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)

Introduction to R

In a world where data is becoming increasingly important, business people and scientists need tools to analyze and process large volumes of data efficiently. R is one of the tools that has become increasingly popular in recent years for data processing, statistical analysis, and data science, and while R has its roots in academia, it is now used by organizations across a wide range of industries and geographical areas.

Some of the important topics covered in this chapter are as follows:

  • History of R and why it was designed the way it was
  • What the interpreter and the console are and how to use them
  • How to work with basic data types and data structures of R
  • How to divide work by using functions in different ways
  • How to introduce complex logic with control structures