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Learning Shiny

You're reading from   Learning Shiny Make the most of R's dynamic capabilities and implement web applications with Shiny

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781785280900
Length 246 pages
Edition 1st Edition
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Authors (2):
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Hernan Resnizky Hernan Resnizky
Author Profile Icon Hernan Resnizky
Hernan Resnizky
Hernan Resnizky Hernan Resnizky
Author Profile Icon Hernan Resnizky
Hernan Resnizky
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Table of Contents (13) Chapters Close

Preface 1. Introducing R, RStudio, and Shiny FREE CHAPTER 2. First Steps towards Programming in R 3. An Introduction to Data Processing in R 4. Shiny Structure – Reactivity Concepts 5. Shiny in Depth – A Deep Dive into Shiny's World 6. Using R's Visualization Alternatives in Shiny 7. Advanced Functions in Shiny 8. Shiny and HTML/JavaScript 9. Interactive Graphics in Shiny 10. Sharing Applications 11. From White Paper to a Full Application Index

Including a plot in a Shiny application


When we include graphics inside a Shiny application, all the elements that are seen can be handled within a reactive context. Taking the same previous example, in the following code, you will see how to use reactivity inside graphical parameters.

In this case, a fixed color is assigned to every species, so the color assignment can be done outside the reactive context. In this case, we will be doing it inside global.R because the inputs in UI.R are going to be defined as the levels of iris$Species, as it was explained in Chapter 4, Shiny Structure – Reactivity Concepts:

global.R# Load Data
data(iris)

#Assign color by Species
iris$color <- sapply(iris$Species, function(x) switch(as.character(x),
setosa = "red",
versicolor = "green",
virginica = "blue"))

UI.R has two types of inputs; firstly, the species (within checkboxGroupInput) and secondly, the variables in the horizontal and vertical axes respectively. For the purpose of simplicity, the first...

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