The first thing to note is that Shiny programs are the easiest to build and understand using two scripts, which are kept within the same folder. They should be named server.R and ui.R. Throughout this book, all code will have the commented server.R and ui.R headers to indicate which code goes in which file. The code is available at github.com/ChrisBeeley/basicGoogleAnalytics2ndEdition.

library(shiny)                             # Line 1
shinyUI(fluidPage(                         # Line 2
  titlePanel("Minimal application"),       # Line 3
  sidebarLayout(                           # Line 4
    sidebarPanel(                          # Line 5
      textInput...

Before we move on to a more advanced application, let's have a look at the main widgets that you will make use of within Shiny. I've built a Shiny application that will show you what they all look like, as well as showing their outputs and the type of data they return. To run it, just enter the following command:

> runGist(6571951)

This is one of the several built-in functions of Shiny that allow you to run code hosted on the Internet. Details about sharing your own creations in other ways are discussed in Chapter 7, Sharing Your Creations. The finished application looks like the following:

You can see the function names (checkboxGroupInput and checkboxInput) as numbered entries on the left-hand side of the panel; for more details, just type ?checkboxGroupInput at the console.

If you're curious about the code, it's available at gist.github.com/ChrisBeeley/6571951.

Now that we've got the basics, let's build something useful. We're going to build an application that allows you to interactively query data from the Google Analytics API. There is no room within this book to discuss registering for and using the Google Analytics API; however, you will very likely wish to make use of the wonderful RGoogleAnalytics package if you want to get your own Analytics data into R. This package is on CRAN and can therefore be installed as usual by running install.packages("RGoogleAnalytics").

To keep things simple, we will concentrate on data from a website that I worked on. We'll also use a saved copy of the data that is loaded into the application the first time it runs. A full production of the application could obviously query the API every time it is launched or on a daily or weekly basis, depending on how many users you expect (the API limits the number of daily queries from each application).

In this chapter, we have covered the most simple of the layout features in Shiny with the help of the sidebarLayout(), mainPanel(), and tabsetPanel() functions. In later chapters, we will build larger and more complex applications, including dashboards, and make use of more advanced layout features. It is worth pausing here briefly to take a quick look at the other types of layout that are available, so you can think about the best way to implement your own application as we go through the next couple of chapters.

There are essentially two more broad types of layout function that you can use in Shiny. The first uses the layout features of Bootstrap and allows you to precisely define the layout of your application using a grid layout. Essentially, Bootstrap asks you to define the UI as a series of rows. Each row can be further subdivided into columns of varying widths.

Each set of columns on a row has widths that add up to 12. In this way one can quite easily specify...

In this chapter we have covered a lot of ground. We've seen that Shiny applications are generally made up of two files: server.R and ui.R. You've learned what each part of the code does, including setting up ui.R with the position and type of inputs and outputs and server.R with the data processing functions, outputs, and any reactive objects that are required.

The optional exercises have given you a chance to experiment with the code files in this chapter, varying the output types, using different widgets, and reviewing and adjusting their return values as appropriate. You've learned about the default layout in Shiny, sidebarLayout(), as well as about the use of mainPanel() and tabsetPanel().

You've also learned about reactive objects and we've discussed when you might use reactive objects. There's more on finely controlling reactivity later in the book.

In the next chapter you're going to learn how to integrate Shiny with your own content, using HTML, CSS, and JavaScript.