Web Application Development with R Using Shiny - ebook

Analyze, communicate, and design your own sophisticated and interactive web applications using the R (v 3.4) Shiny (1.1.0) package

Key FeaturesExplore the power of R Shiny to make interactive web applications easilyCreate engaging user interfaces using elements such as HTML5 shiny tags and TtabsetsBuild and deploy your interactive Shiny web application using shinyapps.ioBook Description

Web Application Development with R Using Shiny helps you become familiar with the complete R Shiny package. The book starts with a quick overview of R and its fundamentals, followed by an exploration of the fundamentals of Shiny and some of the things that it can help you do. You’ll learn about the wide range of widgets and functions within Shiny and how they fit together to make an attractive and easy to use application.

Once you have understood the basics, you'll move on to studying more advanced UI features, including how to style apps in detail using the Bootstrap framework or and Shiny's inbuilt layout functions.

You'll learn about enhancing Shiny with JavaScript, ranging from adding simple interactivity with JavaScript right through to using JavaScript to enhance the reactivity between your app and the UI.

You'll learn more advanced Shiny features of Shiny, such as uploading and downloading data and reports, as well as how to interact with tables and link reactive outputs. Lastly, you'll learn how to deploy Shiny applications over the internet, as well as and how to handle storage and data persistence within Shiny applications, including the use of relational databases.

By the end of this book, you'll be ready to create responsive, interactive web applications using the complete R (v 3.4) Shiny (1.1.0) suite.

What you will learnHarness the power of JavaScript to customize your applicationsBuild dashboards with predefined UI and layoutsEngage your users and build better analytics using interactive plotsLearn advanced code patterns to make your applications easy to write and maintain.Develop a full understanding of Shiny's UI functions to give you the power to build a wide variety of attractive applications.Store data and interact with databases with Shiny.Learn how to share your Shiny applicationsUnderstand reactivity at the conceptual level to build more efficient and robust appsWho this book is for

Web Application Development with R Using Shiny is for you if you are interested in creating compelling web applications and interactive data visualization over the web using Shiny. Programming experience with R is required.

Chris Beeley has been using R and other open source software for ten years to better capture, analyze, and visualize data in the healthcare sector in the UK. He is the author of Web Application Development with R Using Shiny. He works full-time, developing software to store, collate, and present questionnaire data using open technologies (MySQL, PHP, R, and Shiny), with a particular emphasis on using the web and Shiny to produce simple and attractive data summaries. Chris is working hard to increase the use of R and Shiny, both within his own organization and throughout the rest of the healthcare sector, as well to enable his organization to better use a variety of other data science tools. Chris has also delivered talks about Shiny all over the country. Shitalkumar R. Sukhdeve is a senior data scientist at PT Smartfren Telecom Tbk, Jakarta, Indonesia. On his career journey, he has worked with Reliance Jio as a data scientist, entrepreneur, and corporate trainer. He has trained over 1,000 professionals and students and has delivered over 200 lectures on R and machine learning. Research and development in AI-driven self-optimizing networks, predictive maintenance, optimal network quality, anomaly detection, and customer experience management for 4G LTE networks are all areas of interest to Shitalkumar. He is very experienced with R, Spark, R Shiny, H2O, Python, KNIME, the Hadoop ecosystem, MapReduce, Hive, and configuring the open source R Shiny server for machine learning models and dashboard deployment.