Learning Shiny

Table of Contents

Learning Shiny

Credits

About the Author

Acknowledgements

About the Reviewers

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Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Introducing R, RStudio, and Shiny

About R

Installing R

A quick guide to R

About RStudio

Installing RStudio

A quick guide to RStudio

About Shiny

Installing and loading Shiny

Summary

2. First Steps towards Programming in R

Object-oriented programming concepts

Variables in R

Classes in depth

Vectors

Lists

Matrices and arrays

Data frames

Factors

Element selection

Selecting elements from vectors

Selecting elements from arrays

Selecting elements from lists

Selecting elements from data frames

Control structures in R

The if...else block

The while loop

The for loop

The switch statement

Reading data

Delimited data

Reading line by line

Reading a character set

Reading JSON

Reading XML

Reading databases – SQL

Reading data from external sources

Summary

3. An Introduction to Data Processing in R

Sorting elements

sort() versus order()

Basic summary functions

grep and regular expressions

A brief introduction to regular expressions

Sets

Shortcuts

Dot

Non-printable characters

Negation

Alternation

Quantifiers

Special quantifiers

Anchors

Expressions

Escapes

Examples

Example 1

Example 2

The lapply, vapply, sapply, and apply functions

Examples

plyr

The data.table package

reshape2

Summary

4. Shiny Structure – Reactivity Concepts

Shiny as a package

An introduction to server.R and UI.R

UI.R as a JavaScript/HTML wrapper

Including HTML within UI.R

The concept of reactivity

Reactive independent processes within an application

An introduction to global.R

Running a Shiny web application

An overview of simple examples

Example 1 – a general example of how render-like functions work

Example 2 – using reactive objects

Example 3 – Loading data outside reactive context

Example 4 – using global.R

Summary

5. Shiny in Depth – A Deep Dive into Shiny's World

UI.R

The structure

conditionalPanel() – Example 1

conditionalPanel() – Example 2

An example on the use of tabPanel() in tabsetPanel()

Inputs

Free inputs

Lists

Dates

Files

Buttons

submitButton() with conditionalPanel()

downloadButton() - an example

Optimal usage of server.R and global.R

Shiny options

Summary

6. Using R's Visualization Alternatives in Shiny

The graphics package

Barplot

Histograms

Boxplots

Pie charts

Points

Lines

Plotting options

Legends

Plotting a fully customized plot with the graphics package

Including a plot in a Shiny application

A walk around the googleVis package

googleVis in R

An overview of some functions

Candlesticks

Geolocalized visualizations

Treemaps

Motion chart

googleVis in Shiny

A small example of googleVis in Shiny

ggplot2 – first steps

ggplot's main logic – layers and aesthetics

Layers

Aesthetics

Some graphical tools in ggplot2

geom_point

geom_line

geom_bars

An applied example with multiple layers

ggplot and Shiny

Summary

7. Advanced Functions in Shiny

The validate() function

The isolate() function

The observe() function

The reactiveValues() function

Input updates

Summary

8. Shiny and HTML/JavaScript

The www directory

Creating UIs from plain HTML

The use of tags in UI.R

JavaScript

CSS

Other tags

Relating HTML/JavaScript and server.R

Summary

9. Interactive Graphics in Shiny

Interaction possibilities within R graphics

D3.js integration

What is D3?

networkD3

An introduction to htmlwidgets

D3BarChart.R

D3BarChart.js

D3BarChart.yaml

Summary

10. Sharing Applications

runGist/runGitHub/runUrl

shinyapps.io

Deploying applications on your own server

Installing R

Installing the RStudio server

Installing the Shiny package

run_as

listen

location

site_dir/app_dir

directory_index

Summary

11. From White Paper to a Full Application

Problem presentation

Conceptual design

Pre-application processing

Workclass

global.R coding

global.R

UI.R partial coding

UI.R

server.R coding

Gender bar chart

Age chart

Ethnic bar chart

Marital status

Education curve

Earnings chi-square test

Activity summary

UI.R completion

UI.R

Styling

Discovering insights in the application

Summary

Reference

Index

Learning Shiny

Learning Shiny

Copyright © 2015 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: October 2015

Production reference: 1141015

Published by Packt Publishing Ltd.

Livery Place

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ISBN 978-1-78528-090-0

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Credits

Author

Hernán G. Resnizky

Reviewers

Dean Attali

William Kyle Hamilton

Achyutuni Sri Krishna Rao

Commissioning Editor

Kunal Parikh

Acquisition Editors

Shaon Basu

Larissa Pinto

Content Development Editor

Ritika Singh

Technical Editor

Shiny Poojary

Copy Editor

Kausambhi Majumdar

Project Coordinator

Judie Jose

Proofreader

Safis Editing

Indexer

Rekha Nair

Graphics

Disha Haria

Production Coordinator

Melwyn D'sa

Cover Work

Melwyn D'sa

About the Author

Hernán G. Resnizky is a data scientist who is actually working as a freelance consultant in Argentina. He has worked for national and international clients from diverse industries in different domains related to data handling and analysis, such as data visualization, text mining, machine learning modeling, and so on. For over two years, he worked as a senior data scientist for Despegar (http://www.despegar.com/), the leading online travel agency in Latin America.

Regarding his academic background, Hernán has completed a licentiate degree (a five-year study program that is equivalent to a bachelor's and a master's degree) in sociology from the University of Buenos Aires. Also, he has completed his masters of science courses in data mining from the same university.

Hernán has a blog, www.hernanresnizky.com, where he writes about data science and R-related topics. Also, he has reviewed Web Application Development with R Using Shiny for Packt Publishing in the past.

Acknowledgements

I think it would be totally unfair if I didn't start this acknowledgement by thanking the whole R community, as I believe that a considerable part of my knowledge of R and Shiny was gained from gathering information from forums, blogs, and tutorials. In this sense, if I had to think of someone in particular, I should thank Hadley Wickham not only for his packages, but also for his wonderful tutorials, and from RStudio's Shiny crew, I would like to thank Joe Cheng and Winston Chang for their constant efforts to make the Shiny project grow by answering questions, posting articles, and even sharing their repositories.

I would also like to dedicate this book to my former colleagues at Despegar (http://www.despegar.com/) where I spent over two years of constant learning facing new challenges every day, to my clients who believe in my capabilities every day, and to my former classmates and professors at the University of Buenos Aires.

Of course, I can't leave out my family and friends, who despite not understanding completely what I do for a living, always encouraged me to carry on. Finally, I would like to thank my girlfriend for supporting me in this enriching but tough process of writing a book.

About the Reviewers

Dean Attali is a software engineer, technical consultant, and freelance technical writer. He studied computer science at the University of Waterloo, Canada, and has years of experience working for large companies (Google and IBM) as well as small startups (tagged.com, wish.com, and, glittr.com). After spending a few years in San Francisco and getting a good taste of the Silicon Valley tech life, Dean was curious to see what academia had to offer and went on to pursue a master's degree from the University of British Columbia in Vancouver, Canada.

Dean was introduced to R while he was in graduate school, and he quickly developed a passion for R and open source, with a special interest in the Shiny framework. He is now an active member of the R community and is the author of several R packages, most notably shinyjs.

Apart from coding, Dean is also addicted to playing soccer, travelling at any given (and nongiven) moment, getting into philosophical debates, and meeting new people. You can learn more, or just say hello, by visiting him at http://deanattali.com.

William Kyle Hamilton earned his bachelor of arts degree in psychology with a minor in political science from the University of California, Merced in 2012 and is now a PhD student in the Health Psychology program at the University of California, Merced. In addition to this, William runs workshops for academic requesters who wish to use Amazon Mechanical Turk for their studies. William is a community member of the rOpenSci group and has authored the R packages: IRTShiny, MAVIS, RCryptsy, and RStars. Additionally, William serves as a board member for the UC Merced Alumni Association, as well for the Merced County Advisory Board on Alcohol and Drug Problems.

Achyutuni Sri Krishna Rao is an R programmer, data scientist, and civil engineer with more than 4 years of work experience in the public sector and corporate companies. Currently, he is a data scientist associate consultant in one of the leading pharmaceutical consultant firms. He loves to work in the domain of healthcare, power, and construction industry. He strongly believes in the application of Big Data-driven solutions in sectors heavily dominated by core engineering principles.

With a master's in Enterprise Business Analytics from NUS, Achyutuni is a freelancer and R code blogger too. He blogs about providing holistic analytical solutions on open source data using a multitude of machine learning algorithms in R. He is also a corporate trainer in R programming.

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Preface

R is a growing language that is gaining more and more space among data scientists. With over 7,000 packages, you can cover every stage within R: from data extraction, cleansing, and processing to advanced analysis, modelling, or visualization. In this context, Shiny is the tool that will take your R code to the next level, as you will be able to share all your outcomes with anyone through a dynamic web application. Shiny is not just a dashboard tool, but it is the gateway to unveiling hidden facts about data, even for nonexpert users. In other words, developing a Shiny application is like providing access to the R universe.

What this book covers

Chapter 1, Introducing R, RStudio, and Shiny, is a brief introduction to R, RStudio, and Shiny, and it contains the necessary information to install them.

Chapter 2, First Steps towards Programming in R, is a general introduction to some key concepts and basic operations in R.

Chapter 3, An Introduction to Data Processing in R, covers some techniques to clean and process data in R using the functions of specific packages. Data processing is definitely one of the key aspects to take into account in order to produce a successful application.

Chapter 4, Shiny Structure – Reactivity Concepts, introduces the reader to Shiny's internal structure and logic.

Chapter 5, Shiny in Depth – A Deep Dive into Shiny's World, examines the different possibilities within the Shiny structure for each of its components. For the user interface section, it presents the different elements available, and for the backend section, it gives some hints about how to optimally organize code.

Chapter 6, Using R's Visualization Alternatives in Shiny, covers the most important graphical packages in R and how to include their outcomes in a Shiny application. This is a key aspect when developing an application, as graphics are usually one of the most common ways to present information in a web application.

Chapter 7, Advanced Functions in Shiny, introduces some advanced functions to control more complex interactions and explains how to use them.

Chapter 8, Shiny and HTML/JavaScript, explains how to include custom JavaScript, HTML, and CSS code in a Shiny application, as Shiny's frontend is HTML-based/JavaScript-based.

Chapter 9, Interactive Graphics in Shiny, covers two topics, whose common root is interaction with graphics. Firstly, the newly released functionality of Shiny's event listener within R's standard graphics and then the generation of custom JavaScript visualizations, and how to include them in a Shiny application.

Chapter 10, Sharing Applications, introduces different possibilities to publish applications right from passing the entire code to uploading it to a server and making it accessible via URL.

Chapter 11, From White Paper to a Full Application, simulates a real-world situation where a web application is needed and explains the whole process from scratch in a holistic way. It not only explains the code, but also gives some tips about how to structure it and how to communicate with data.

What you need for this book

The software used in this book is free and open source and is available for Linux, Mac, and Windows. An internet connection is necessary for some of the topics covered in this book.

Who this book is for

This book is suitable even for readers with no experience in R, Shiny, or HTML at all. However, having some previous knowledge in any of these fields will definitely be an advantage to understand this book quickly.

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: If it is a .rda or .RData file, it will open in both.

A block of code is set as follows:

#Load XML library

library(XML)

#URL Public API Worldbank Data Catalog in XML format

url <- http://api.worldbank.org/v2/datacatalog?format=xml

#Load XML document

xml.obj <- xmlTreeParse(url)

Any command-line input or output is written as follows:

> class(xml.obj) [1] XMLDocument    XMLAbstractDocument

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: In RStudio, whenever a function is declared, it will appear in the Environment section under the Functions section:

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

Reader feedback

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