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)

Styling our application with themes

Up to this point, we have been using the theme provided by default by Shiny, but now that our application is finished, we want to stylize it with some tech-looking colors. In that case, we can use the shinythemes and ggthemr packages, which provide us with an easy way to apply themes to Shiny applications and ggplot2 graphs, respectively.

All we need to do to apply the themes is to tell the ggplot2 framework to apply the flat dark theme provided by the ggthemr package, and to make sure that the outer side of the graph is also stylized we use the type = outer parameter, as is shown here. The code should be placed wherever we placed our ggplot2 code for cohesiveness, which is in the functions.R file for this chapter:

library(ggthemr)
ggthemr('flat dark', type = 'outer')

To stylize the Shiny application itself, we send the theme...