Coding in R for Policy Analytics


This lab gently introduces how to create an interactive dashboard in R.

You can create a new R Markdown file, or download the LAB-03 RMD templates:



Overview

Lab 04 builds on the static graphic created in Lab 03 by rendering key graphical elements, such as the trendline and legend, as interactive and responsive to user inputs, just like any other app. Visit the final app by clicking here.


The Lab 03 Gapminder visualization as an interactive app.



Dynamic Graphics

Recall that Shiny allows you to build interactive data products. An app’s interactivity occurs between user input and machine output.

Note that in the server code, any dynamic code must be within a “reactive context”, which typically lies within curly brackets, or { ... }.



Assignment Requirements

In addition to modifying your dashboard with your name, Lab 04 requires the following:

  1. Add the Lab 03 visualization code in the server/chunk
  2. Add an additional trendline to your graphic representing a user-selected region
  3. Add a selectInput() control function to the app UI and connect it to the server


In addition, you must install and load the following packages in your script.

library(shiny)
library(tidyverse)
library(flexdashboard)
library(shinydashboard)


Adding the Lab 03 Code

Regardless of what visualization or Shiny packages you use, you must place your Lab 03 visualization code within a renderPlot() function.


Adding a Trend Line

Depending on which visualization package you choose, you will need to append a new trend line differently.

  • For ggplot2, consider using geom_line() or geom_path()
  • For graphics, consider using points() or lines()

Note that the trend line will contain the “reactive” shiny input. You only need to experiment with this part of the visualization code to be successful.


Adding & Connecting Input Controls

Regardless of your visualization or dashboard packages used, you must use base Shiny function selectInput() and list all possible regions as well as a default selection.

Recall that the inputId = argument accepts a character string that becomes a unique identifier. When this ID is used in conjunction with input$, i.e.  input$id, it acts as an object representing whatever value is chosen in selectInput().

For example, if you choose “Europe East” in the UI with selectInput(inputId = "my_example"), then the server’s input$my_example now represents and acts as the value “Europe East”.



Shiny Package Differences

Templates are provided to complete your dashboard using any of the following packages:

Note that you need only use one, though all options will require shiny.


Package ‘shiny’

Function selectInput() should be placed within sidebarPanel().


Package ‘flexdashboard’

The location of selectInput() is provided.


Package ‘shinydashboardplus’

Function selectInput() should be placed within sidebarMenu().




How to Submit

You need only submit your .Rmd file for this week.


Before You Submit

Remember to ensure the following before submitting your assignment.

  1. Name your files using this format: Lab-##-LastName.rmd
  2. Follow appropriate styling conventions, e.g. spaces after commas, etc.
  3. Above all, ensure that your conventions are consistent

See Google’s R Style Guide for examples of common conventions.