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Learning Shiny

Learning Shiny

By : Hernan Resnizky
2.9 (7)
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Learning Shiny

Learning Shiny

2.9 (7)
By: Hernan Resnizky

Overview of this book

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.
Table of Contents (13 chapters)
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1
1. Introducing R, RStudio, and Shiny
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12
Index

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:

A quick guide to R

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

A quick guide to R

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.

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