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)

Understanding why R can be slow

Understanding why a programming language can be slow is a fundamental skill needed to be able to increase the speed of its implementations. Any implementation in any programming language is similarly affected by an algorithm's time and memory complexities, because they are algorithms, and not implementation properties. However, the way languages handle specific implementations can vary quite a bit, and that's what we'll focus on now.

In the case of R, people often find the following four main bottlenecks:

  • Object immutability
  • Interpreted dynamic typings
  • Memory-bound processes
  • Single-threaded processes

By no means is this list complete or encountered in every implementation. It's just the most common bottlenecks I've seen people encounter, and which, after being fixed, produced the largest amount of speed improvements. They...