DSCI 325: Handout 26 Introduction to R Shiny Spring 2017

Transcription

1 DSCI 325: Handout 26 Introduction to R Shiny Spring 2017 Shiny is an R package that allows users to build interactive web applications using R. Programming in Shiny is more involved than using the manipulate function, but it also offers more flexibility and is worth the extra effort. RStudio has put together an excellent tutorial on Shiny: Much of this handout is based on this tutorial. To begin, you ll need to install and load the Shiny package: > install.packages("shiny" > library("shiny" The Structure of a Shiny App Shiny apps consist of two components: A user-interface script ( A server script (server.r The user-interface script defines the layout and appearance of your app. The server script, on the other hand, contains the R code your computer needs to build your app. The code below shows the bare minimum needed to create a Shiny app. server.r shinyserver(function(input, output { } Running a Shiny App To create an app, these two scripts must be saved together in a directory. In RStudio, you can create a new app by selecting File > New File > Shiny Web App In the dialog box that appears, name your app and specify its directory (each app needs its own unique directory. The dialog box shown below will create an app named FirstApp that will be saved in the specified folder. Note that we are creating a multiple file application type; you can also create a single file application type. You can learn more about single file apps here. 1

2 To create the app, save the above and server.r scripts inside the FirstApp folder. Then, you can run the app by passing the name of its directory to the function runapp. In order for this to work, the working directory in the R session must be set to the directory containing the application. > setwd("q:/dsci 325/Intro_to_R/R Shiny" > runapp("firstapp" An alternative is to set your working directory to the application s folder, itself. If you do this, you should not specify the app s name in the runapp function. > setwd("q:/dsci 325/Intro_to_R/R Shiny/FirstApp" > runapp( The result is an empty app with a blank user-interface. The app is shown by default in normal mode. You can alternatively display the app in showcase mode, which will display the source code in addition to the user-interface. > setwd("q:/dsci 325/Intro_to_R/R Shiny" > runapp("firstapp", display.mode="showcase" 2

3 Building a Basic User-Interface The script uses the fluidpage function to create the app s display. You can lay out the app by placing elements in the fluidpage function. For example, let s modify the script in our app named FirstApp. Make the changes shown below and save the user-interface script. titlepanel("first Shiny App", sidebarpanel( sidebar panel, mainpanel( main panel Now, when you re-run the app, you should see the following: The titlepanel and sidebarlayout are the two most popular elements to add to fluidpage. They create a basic Shiny app with a sidebar. The sidebarlayout function takes two arguments: sidebarpanel function output mainpanel function output These place content in the panels of the user-interface. The sidebar is displayed with a distinct background color and typically contains input controls. The main area typically contains outputs. Note that you can move the sidebar panel to the right side of the interface using the optional argument position= right : titlepanel("first Shiny App", position= right, sidebarpanel( sidebar panel, mainpanel( main panel 3

4 The app now appears as follows: Options do exist to create more advanced layouts. For example, navbarpage allows you to create a multi-page user-interface that includes a navigation bar. Or, fluidrow and column can be used to build the layout up from a grid system. Adding Control Widgets Control widgets can be used to collect a value from the app s user. When the user changes the widget, the value changes, as well. Several pre-built widgets are available in Shiny: Function actionbutton checkboxgroupinput checkboxinput dateinput daterangeinput fileinput helptext numericinput radiobuttons selectinput sliderinput submitbutton textinput Widget Action Button A group of check boxes A single check box A calendar to aid date selection A pair of calendars for selecting a date range A file upload control wizard Help text that can be added to an input form A field to enter numbers A set of radio buttons A box with choices to select from A slider bar A submit button A field to enter text You can add control widgets to your app by placing one of the above functions in either the sidebarpanel or mainpanel functions in the file. Each widget function requires at least these first two arguments: a name for the widget (you will use this to access the widget s value a label (this will appear with the widget in your app; note that it can be an empty string 4

5 For example, consider the following modification to the user-interface script for FirstApp. titlepanel("first Shiny App", sidebarpanel( sliderinput("obs", "Number of observations:", min=0, max=100, value=50, mainpanel("main panel" Once these changes are made and the user-interface script is saved, we see the following when we run the app: Displaying Reactive Output Shiny is built on the idea of reactive programming (outputs are automatically updated when an input value changes. Reactive output is created with a two-step process: 1. Add an R object to your user-interface with. 2. Tell Shiny how to build the object in server.r. The object will be reactive if the code used to build it calls a widget value. The following functions turn R objects into output for your user-interface. Output Function htmloutput imageoutput plotoutput Creates Raw HTML Image Plot 5

6 Output Function tableoutput textoutput uioutput verbatimtextoutput Creates Table Text Raw HTML text Once again, you can add output to the user-interface by placing one of the above output functions in either the sidebarpanel or mainpanel functions in the script. Placing an output function in the file tells Shiny where to display your object, but you still need to tell it how to build your object. This happens in the unnamed function that appears inside the server.r script. This unnamed function builds a list-like object named output that contains all of the code needed to update the R objects in your app. You can create an entry by defining a new element for output within the unnamed function (the name of this element should match the name of the reactive element created in. For example, the following scripts together create a plot in the app s output. titlepanel("first Shiny App", sidebarpanel( sliderinput("obs", "Number of observations:", min=0, max=100, value=50, mainpanel( plotoutput("distplot" server.r shinyserver(function(input, output { output$distplot <- ## assignment statements } What should the assignment statements mentioned in the above server.r script look like? Each entry to output should contain the output of one of Shiny s render functions. 6

7 Render Function renderimage renderplot renderprint rendertable rendertext renderui Creates Images Plots Any printed output Data frame, matrix, other table-like structures Character strings A Shiny tag object or HTML For example, consider modifying our app to plot a histogram of 100 observations which are randomly drawn from the normal distribution. titlepanel("first Shiny App", sidebarpanel( sliderinput("obs", "Number of observations:", min=0, max=100, value=50, mainpanel( plotoutput("distplot" server.r shinyserver(function(input, output { output$distplot <- renderplot({ dist <- rnorm(n = 100 histogram(dist } } When the app is run, the following is displayed: 7

8 When the previous server.r script is submitted, the app displays the plot; however, the plot is not yet reactive. To make it react to the slider bar, you must ask Shiny to call a widget value when it builds the plot. This is accomplished using the input object. The current values of all widgets in your app are saved under the names that were assigned to the widgets in the script. titlepanel("first Shiny App", sidebarpanel( sliderinput("obs", "Number of observations:", min=0, max=100, value=50, mainpanel( plotoutput("distplot" server.r shinyserver(function(input, output { output$distplot <- renderplot({ dist <- rnorm(n = input$obs histogram(dist } } Now, the plot will update when the slider bar is moved. Tasks: 1. Modify the app so that you can simulate up to 1000 observations. Start your slider bar at Add a numeric input to change the mean and standard deviation of the normal distribution from which the random sample is taken. 3. Add an input that allows you to simulate data from either a standard normal distribution (with mean = 0 and standard deviation = 1 or a gamma distribution with shape parameter = 1 (you can use the rgamma function. This app should allow you to choose the number of observations, as well. 8