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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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Toc

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

Object-oriented programming concepts


As in any other object-oriented programming language, a class in R is an abstract definition of an object type with specific attributes associated to it. For instance, for an eventual dog class (which is a general definition of a dog), we could say that it has the color, size, age, and so on attributes.

An object is an instance of a specific class. Continuing with the previous example, we could have a Dog1 object whose attributes can be the following:

  • color: "brown"

  • size: 5.5 inch

  • age: 3 years

In R, the attributes of an object can be accessed by typing attr(object, "attribute"), for instance:

data(iris)
attributes(iris)

In this example, a data frame object (data frame objects will be explained later in this chapter) called iris is loaded, which has the names, row.names, and class attributes (R considers the class of an object an attribute as well). In most cases, many of the values for these attributes in a particular object can be accessed by typing either...

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