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)

Exploring with interactive 3D scatter plots

When exploring data, sometimes it's useful to look at a 3D scatter plot. However, if the scatter plot is fixed (meaning that you cannot move it around), it may not be easy to interpret. Having an interactive plot (one you can move around) to see different angles of the data is very useful in these cases. These graphs don't normally go into static reports because they are hard to interpret correctly when fixed, but are very useful to do data exploration. Luckily, they are also very easy to create with the plot3d() function from the rgl package:

library(rgl)
plot3d(sales$PROTEIN, sales$CARBS, sales$FAT)
plot3d(sales$PROFIT_RATIO, sales$PRICE, sales$QUANTITY)

Once you create these plots in your computer, remember to move them around with your mouse! The first time you do this, it's pretty amazing. In this case, you can see...