In the first chapter, you'll review the essentials of Shiny development. You'll get reintroduced to the basic structure of a Shiny application, as well as some core Shiny concepts such as inputs, outputs, and reactivity. Completing this chapter will help refresh your Shiny knowledge and ensure you have the required skills to develop Shiny apps for real-life scenarios.
Imagine you're preparing a figure for a manuscript using R. You spend a lot of time recreating the same plot over and over again by rerunning the same code but changing small parameters each time. The size of the points, the color of the points, the plot title, the data shown on the plot—these criteria all have to be just right before publishing the figure. To save you from the hassle of rerunning the code many times, you will learn how to create a Shiny app to make a customizable plot.
Let’s say your supervisor is impressed by the plot you created with Shiny and now wants to get familiar with the dataset you used in the plot. They don't want to simply have a raw data file, they want an interactive environment where they can view the data, filter it, and download it. This chapter will guide you in creating such an application—a Shiny app for exploring the Gapminder dataset.
Your friend really likes word clouds and has written an R function to generate them. They want to share this function with all their friends, but not all of them know how to use R. You offer to help by building a Shiny app that uses their function to let people create their own word clouds. This will allow all their friends—even the ones who are unfamiliar with R—to generate word clouds using a point-and-click interface. This chapter will guide you through the steps required to build this app.