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)

Scatter plots with joint and marginal distributions

We have seen how to create scatter plots with ggplot() in previous chapters. Therefore, in this section, we will only focus on the parts that we have not seen before. Our objective is to create scatter plots that not only show the scatter plot, but extend it by showing the marginal distributions on both axes. These are called marginal plots and are useful for understanding how data is jointly (two variables) as well as marginally (one variable) distributed.

Pricing and profitability by protein source and continent

As usual, we start developing our graph function. We receive as parameters the data, and the variables for the x axis (x) and y axis (y), and, in this case, we...