What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

Learning Shiny

Chapter 1. Introducing R, RStudio, and Shiny

In this chapter, the main objective will be to learn how to install all the needed components to build an application in R with Shiny. Additionally, some general ideas about what R is will be covered in order to be able to dive deeper into programming using R.

The following topics will be covered in this chapter:

A brief introduction to R, RStudio, and Shiny
Installation of R and Shiny
General tips and tricks

About R

As stated on the R-project main website:

"R is a language and environment for statistical computing and graphics."

R is a successor of S and is a GNU project. This means, briefly, that anyone can have access to its source codes and can modify or adapt it to their needs. Nowadays, it is gaining territory over classic commercial software, and it is, along with Python, the most used language for statistics and data science.

Regarding R's main characteristics, the following can be considered:

Object oriented: R is a language that is composed mainly of objects and functions. Chapter 2, First Steps towards Programming in R, and Chapter 3, An Introduction to Data Processing in R, will cover object and function handling in R.
Can be easily contributed to: Similar to GNU projects, R is constantly being enriched by users' contributions either by making their codes accessible via "packages" or libraries, or by editing/improving its source code. There are actually almost 7000 packages in the common R repository, Comprehensive R Archive Network (CRAN). Additionally, there are other R repositories of public access, such as the bioconductor project which contains packages for bioinformatics.
Runtime execution: Unlike C or Java, R does not need compilation. This means that you can, for instance, write 2 + 2 in the console and it will return the value.
Extensibility: The R functionalities can be extended through the installation of packages and libraries. Standard proven libraries can be found in CRAN repositories and are accessible directly from R by typing install.packages().

Installing R

R can be installed in every operating system. It is highly recommended to download the program directly from http://cran.rstudio.com/ when working on Windows or Mac OS. On Ubuntu, R can be easily installed from the terminal as follows:

sudo apt-get update
sudo apt-get install r-base
sudo apt-get install r-base-dev

The installation of r-base-dev is highly recommended as it is a package that enables users to compile the R packages from source, that is, maintain the packages or install additional R packages directly from the R console using the install.packages() command.

To install R on other UNIX-based operating systems, visit the following links:

A quick guide to R

When working on Windows, R can be launched via its application. After the installation, it is available as any other program on Windows. When opening the program, a window like this will appear:

When working on Linux, you can access the R console directly by typing R on the command line:

In both the cases, R executes in runtime. This means that you can type in code, press Enter, and the result will be given immediately as follows:

> 2+2
[1] 4

The R application in any operating system does not provide an easy environment to develop code. For this reason, it is highly recommended (not only to write web applications in R with Shiny, but for any task you want to perform in R) to use an Integrated Development Environment (IDE).

The topics related to the R language are covered mainly in Chapter 2, First Steps towards Programming in R, and Chapter 3, An Introduction to Data Processing in R.

About RStudio

As with other programming languages, there is a huge variety of IDEs available for R. IDEs are applications that make code development easier and clearer for the programmer. RStudio is one of the most important ones for R, and it is especially recommended to write web applications in R with Shiny because this contains features specially designed for this purpose. Additionally, RStudio provides facilities to write C++, Latex, or HTML documents and also integrates them to the R code.

RStudio also provides version control, project management, and debugging features among many others.

Installing RStudio

RStudio for desktop computers can be downloaded from its official website at http://www.rstudio.com/products/rstudio/download/ where you can get versions of the software for Windows, MAC OS X, Ubuntu, Debian, and Fedora.

A quick guide to RStudio

Before installing and running RStudio, it is important to have R installed. As it is an IDE and not the programming language, it will not work at all. The following screenshot shows RStudio's starting view:

At the first glance, the following four main windows are available:

Text editor: This provides facilities to write R scripts such as highlighting and a code completer (when hitting Tab, you can see the available options to complete the code written). It is also possible to include R code in an HTML, Latex, or C++ piece of code.
Environment and history: They are defined as follows:
- In the Environment section, you can see the active objects in each environment. By clicking on Global Environment (which is the environment shown by default), you can change the environment and see the active objects. You can find more information about environments in a chapter dedicated to this topic in the book Advanced R, by Hadley Wickham. It is available at http://adv-r.had.co.nz/Environments.html.
- In the History tab, the pieces of codes executed are stored line by line. You can select one or more lines and send them either to the editor or to the console. In addition, you can look up for a certain specific piece of code by typing it in the textbox in the top right part of this window.
Console: This is an exact equivalent of R console, as described in Quick guide of R.
Tabs: The different tabs are defined as follows:
- Files: This consists of a file browser with several additional features (renaming, deleting, and copying). Clicking on a file will open it in editor or the Environment tab depending on the type of the file. If it is a .rda or .RData file, it will open in both. If it is a text file, it will open in one of them.
- Plots: Whenever a plot is executed, it will be displayed in that tab.
- Packages: This shows a list of available and active packages. When the package is active, it will appear as clicked. Packages can also be installed interactively by clicking on Install Packages.
- Help: This is a window to seek and read active packages' documentation.
- Viewer: This enables us to see the HTML-generated content within RStudio.

Along with numerous features, RStudio also provides keyboard shortcuts. A few of them are listed as follows:

Description	Windows/Linux	OSX
Complete the code.	Tab	Tab
Run the selected piece of code. If no piece of code is selected, the active line is run.	Ctrl + Enter	⌘ + Enter
Comment the selected block of code.	Ctrl + Shift + C	⌘ + /
Create a section of code, which can be expanded or compressed by clicking on the arrow to the left. Additionally, it can be accessed by clicking on it in the bottom left menu.	`#####`	`#####`
Find and replace.	Ctrl + F	⌘ + F

The following screenshots show how a block of code can be collapsed by clicking on the arrow and how it can be accessed quickly by clicking on its name in the bottom-left part of the window:

Clicking on the circled arrow will collapse the Section 1 block, as follows:

The full list of shortcuts can be found at https://support.rstudio.com/hc/en-us/articles/200711853-Keyboard-Shortcuts.

Note

For further information about other RStudio features, the full documentation is available at https://support.rstudio.com/hc/en-us/categories/200035113-Documentation.

About Shiny

Shiny is a package created by RStudio, which enables to easily interface R with a web browser. As stated in its official documentation, Shiny is a web application framework for R that makes it incredibly easy to build interactive web applications with R.

One of its main advantages is that there is no need to combine R code with HTML/JavaScript code as the framework already contains prebuilt features that cover the most commonly used functionalities in a web interactive application. There is a wide range of software that has web application functionalities, especially oriented to interactive data visualization. What are the advantages of using R/Shiny then, you ask? They are as follows:

It is free not only in terms of money but (as with all GNU projects) in terms of freedom. As stated in the GNU main page: To understand the concept, you should think of "free" as in "free speech", not as in "free beer". Free software is a matter of the users' freedom to run, copy, distribute, study, change, and improve the software.
All the possibilities of a powerful language such as R is available. Thanks to its contributive essence, you can develop a web application that can display any R-generated output. This means that you can, for instance, run complex statistical models and return the output in a friendly way in the browser, obtain and integrate data from the various sources and formats (for instance, SQL, XML, JSON, and so on) the way you need, and subset, process, and dynamically aggregate the data the way you want. These options are not available (or are much more difficult to accomplish) under most of the commercial BI tools.

Installing and loading Shiny

As with any other package available in the CRAN repositories, the easiest way to install Shiny is by executing install.packages("shiny").

The following output should appear on the console:

Due to R's extensibility, many of its packages use elements (mostly functions) from other packages. For this reason, these packages are loaded or installed when the package that is dependent on them is loaded or installed. This is called dependency. Shiny (on its 0.10.2.1 version) depends on Rcpp, httpuv, mime, htmltools, and R6.

An R session is started only with the minimal packages loaded. So if functions from other packages are used, they need to be loaded before using them. The corresponding command for this is as follows:

library(shiny)

When installing a package, the package name must be quoted but when loading the package, it must be unquoted.

Description

Make the most of R’s dynamic capabilities and implement web applications with Shiny About This Book Present interactive data visualizations in R within the Shiny framework Construct web dashboards in a simple, intuitive, but fully flexible environment Apply your skills to create a real-world web application with this step-by-step guide Who This Book Is For If you are a data scientist who needs a platform to show your results to a broader audience in an attractive and visual way, or a web developer with no prior experience in R or Shiny, this is the book for you. What You Will Learn Comprehend many useful functions, such as lapply and apply, to process data in R Write and structure different files to create a basic dashboard Develop graphics in R using popular graphical libraries such as ggplot2 and GoogleVis Mount a dashboard on a Linux Server Integrate Shiny with non-R-native visualization, such as D3.js Design and build a web application In Detail R is nowadays one of the most used tools in data science. However, along with Shiny, it is also gaining territory in the web application world, due to its simplicity and flexibility. Shiny is a framework that enables the creation of interactive visualizations written entirely in R and can be displayed in almost any ordinary web browser. It is a package from RStudio, which is an IDE for R. From the fundamentals of R to the administration of multi-concurrent, fully customized web applications, this book explains how to achieve your desired web application in an easy and gradual way. You will start by learning about the fundamentals of R, and will move on to looking at simple and practical examples. These examples will enable you to grasp many useful tools that will assist you in solving the usual problems that can be faced when developing data visualizations. You will then walk through the integration of Shiny with R in general and view the different visualization possibilities out there. Finally, you will put your skills to the test and create your first web application! Style and approach This is a comprehensive, step-by-step guide that will allow you to learn and make full use of R and Shiny’s capabilities in a gradual way, together with clear, applied examples.

What you will learn

Comprehend many useful functions, such as lapply and apply, to process data in R Write and structure different files to create a basic dashboard Develop graphics in R using popular graphical libraries such as ggplot2 and GoogleVis Mount a dashboard on a Linux Server Integrate Shiny with non-R-native visualization, such as D3.js Design and build a web application

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

Frequently bought together

Mastering RStudio: Develop, Communicate, and Collaborate with R

S$74.99

S$59.99

Web Application Development with R Using Shiny Second Edition

S$59.99

Total S$ 194.97

Filter reviews by

All

Amazon verified reviews

M. Rumore Jan 26, 2018

I disagree with the other reviewers. This book is an introduction to Shiny and it covers the case where the reader may also be new to R.It provides an excellent description of the Shiny archictecture, the connection between the UI processing and the data-processing backend. The chapters slowly progress through the various Shiny capabilites with straightforward examples which are easy to understand and demonstrate the interactions between user-input, data processing, UI updates, etc. It also covers (briefly) how to include HTML, CSS, javascript into Shiny applications.The final chapter develops an application where all the parts are linked and demonstrated.If you need more details, then you do have to look elsewhere.

Amazon Verified review

Oscar Jun 11, 2019

Excelente libro

Ray O Light Nov 30, 2015

This is value for money given the technical content of the book.What I liked about the book is that it goes straight to giving the technical knowledge and understanding of Shiny.Where I would think it could be better is to bring the last chapter forward and start off with an overarching view of using Shiny and its Conceptual design (this would help the reader to associate better web design and using Shiny). Also suggest removing the introduction to R portion, which is too brief and not necessary since it is very likely people who wish to learn about Shiny already know R. (started reading straight from chapter 4).Overall, this book is geared more towards the technical aspect and helps to stir interest in picking up Shiny development.

Amazon Customer Nov 19, 2015

There are very rare books written on shiny. It is an introductory book to get you started with Shiny. The book covers very basic examples so do n't expect to have expert skills after reading this book. Chapter 11 From White Paper to a Full Application did nice job in giving an overview of end to end development process.

MR MW GREGORY Oct 10, 2016

Online tutorials provided by R Studio are superior. Provides little additional value for the cost. Probably good if you are new to R and Shiny, not good for advanced users.

Learning Shiny: Make the most of R's dynamic capabilities and implement web applications with Shiny

What do you get with a Packt Subscription?

Learning Shiny

Chapter 1. Introducing R, RStudio, and Shiny

About R

Installing R

A quick guide to R

About RStudio

Installing RStudio

A quick guide to RStudio

Note

About Shiny

Installing and loading Shiny

Summary

Page 1 of 5

Description

What you will learn

Product Details

What do you get with a Packt Subscription?

Product Details

Frequently bought together

Table of Contents

Recommendations for you

Customer reviews

Filter reviews by

People who bought this also bought

About the author

FAQs

Learning Shiny: Make the most of R's dynamic capabilities and implement web applications with Shiny

What do you get with a Packt Subscription?

Installing R

A quick guide to R

Description

What you will learn

Product Details

What do you get with a Packt Subscription?

Product Details

Packt Subscriptions

Frequently bought together

Table of Contents

Recommendations for you

Customer reviews

Filter reviews by

People who bought this also bought

About the author

FAQs