Introduction to R Shiny Dashboarding

June 25–27, AMMnet Senegal Workshop

🎯 Session Objectives

Understand key elements of Shiny Dashbaords

Gain hands on experience customising Shiny dashbaords

We can’t cover all aspects of creating Shiny Dashboards but there are a tonne of great resources online we will share during the course of today!

What is a Dashboard?

A dashboard is a visual interface for exploring and interacting with data.
In public health, dashboards help turn raw data into insights.
Shiny lets you build dashboards directly in R — no web development needed!

📊 You’ve probably seen dashboards used in the COVID-19 response - what other dashboards can you think of?

Why Use Shiny?

✅ Turns R code into interactive web apps
✅ You don’t need to learn HTML, CSS, or JavaScript
✅ Great for sharing visualizations, tables, and summaries
✅ Easy to deploy: share with collaborators or host online
✅ Allow non R users to interact and explore data without the need to code.
✅ Provide analytical capacity to people without analytical skills
✅ Shiny is a lot more flexible that DHIS2 modules

Challenges

🛑 Need an R coding background
🛑 Can be more complext than normal R scripts
🛑 Can be costs to hosting apps for distribution

Examples of Dashboards

Shiny dashbaords can grow to be incredibly complex web applications but can also be small simple tools designed to help colleagues with everyday tasks and problems. Here are two examples of dashboards we’ve created recently at PATH.

🦵💪 Anatomy of a Shiny App

A basic Shiny app has two main parts:

UI (User Interface) – what the user sees and interacts with (frontend)
Server – what R does behind the scenes - computations and tasks based on the user inputs (backend)

library(shiny)
library(bslib)

# Define UI ----
ui <- fluid_page(
 # Define the layout
 # Define the theme 
 # Define user input selection
 # Define types of outputs
)

# Define server logic ----
server <- function(input, output) {
# Computations 
}

# Run the app ----
shinyApp(ui = ui, server = server)

This code is the bare minimum needed to create a Shiny app. The result is an empty app with a blank user interface.

🎨 Theming

Customizing the theme of your dashboard is a really simple way to upgrade the look and feel of your app.

You can use the {bslib} package to easily:

Change colors, fonts, and spacing
Apply modern Bootstrap themes (like flatly, minty, cosmo)
Preview changes live while building your app

We’ll explore this in more detail later — for now, just know it’s easy to give your dashboard a polished, professional look!

📦 Helpful Packages

shiny – the core package
bslib – for modern dashbaord design
tidyverse – for data wrangling
DT – for interactive tables
plotly – for interactive plots
leaflet - for open source interactive maps

🌐 Helpful Webpages for Getting Started with Shiny

Below are some beginner-friendly resources to help you dive deeper into Shiny:

Link	Description
Shiny Get Started	Official step-by-step tutorial for beginners, with hands-on examples.
Shiny Gallery	Explore live examples of Shiny apps with source code.
Mastering Shiny (book)	Free online book by Hadley Wickham covering basics to advanced topics.
Shiny Cheatsheet	Handy reference for Shiny functions and UI elements (download the PDF).
Shiny UI Editor (Experimental)	Drag-and-drop interface to design your UI visually.

These links are a great place to start exploring after today’s session.

What You’ll Build Today: An R Shiny dashboard to visualize routine malaria data

Pull data from DHIS2 ✔
Clean and summarize key indicators ✔
Build simple interactive plots and tables 🔃
Customize 🔃

Key Takeaways

Shiny makes dashboards easy to build in R
You’ll learn by doing — today is all about hands-on practice
You’ll work with a template and build out each element of the dasboard
We’ll go step-by-step 🛠️

Instructions

Follow the link to the materials worksheet - open in google chrome for auto translate.

Work through each section and complete the exercises as you go.

Reach out for help or to ask questions!

Enjoy!!