Visualizations, whether we realise it or not, surround us and are part and parcel of the fabric of our everyday lives. From weather reports to emotive statistics conveyed in new stories, visualizations profoundly shape our cognitive awareness and understanding of reality. But how can social science researchers use them to their advantage?

You might be familiar with graphs and infographics, but visualizations that are interactive, allowing the user to play with and make sense of the data themselves, are a powerful tool to have in your research arsenal. They allow you to present and interpret complex data efficiently and often emotively, presenting a story from your data.

Our Interactive Visualization with R online course was designed to show you how to do just that. Working in R, a popular and free statistical software package, our instructor Martin Hadley from the University of Oxford will demonstrate to you the tools and techniques needed to produce effective interactive visualizations.

The course features the following modules:

Module 1 - Toolkit

Module 1 gives an overview of interactive visualization, and explains how to set up the various toolkits you’ll be using throughout the course

Module 2 - Getting ready

This modules looks at:

  • Typical workflow for interactive visualizations and reports - Overview of the workflow for putting together an interactive visualization and report
  • Planning a story - What needs to be considered when planning visualizations and reports
  • Getting data ready - Coverage of defined tidyverse packages to get data ready for visualization, along with a simple exercise
  • A simple example of a workflow - Preparing data using tidyverse and producing a simple bar chart with plotly

Module 3 - Interactive charts and maps

This module looks at:

  • Producing charts with plotly - More in-depth look at using htmlwidget plotly to make a chart
  • Producing charts with highcharter - Making a chart with highcharter and comparison to plotly
  • Making an interactive map with leaflet and plotly - Creating a map with interactive markers
  • Producing a network chart - Creating a network chart using tibbles and visNetwork

Module 4 - Shiny basics and R markdown

This module looks at:

  • Charts in shiny - Outputting htmlwidget charts in shiny
  • Controls and UI - Adding and configuring controls
  • Reactivity and publishing - Controlling when variables update, and publishing your app
  • Creating an RMarkdown document - Creating the right type of document for your report
  • Adding charts and code - Adding charts, code chunks and shiny apps
  • Publishing - Publishing Rmarkdown documents


The next cohort of Interactive Visualizations with R for Social Scientists starts on July 9th. Find out more and sign up here.