Interactive Visualisation in R

Organised by

Royal Statistical Society


Charlie Hadley


20/04/2021 - 21/04/2021


12 Errol Street


View in Google Maps  (EC1Y 8LX)



This course will introduce two technologies that will fundamentally change your use of R for data presentation on the web: htmlwidgets and Shiny. The first half of the course introduces RMarkdown and htmlwidgets, demonstrating how reports with interactive tables, maps and charts can be written and published to the web using RStudio. The second half of the course introduces the basics of Shiny, a web framework for creating sophisticated interactive applications using only the R language.

Htmlwidgets and Shiny are thoroughly underused in the R community. This course will show you it is almost trivial to build interactive charts/maps/data tables with htmlwidgets and only slightly trickier to build sophisticated interactive applications with Shiny.

Learning Outcomes

  • Recognise the benefits of analysis and visualisation design in RMarkdown document
  • Select appropriate htmlwidgets for data or analytical results and include them in RMarkdown documents
  • Publish RMarkdown reports to the web with RPubs or Github Pages
  • Produce basic Shiny apps incorporating htmlwidgets and publish them to

Topics Covered

  • Overview of the RStudio and tidyverse ecosystem
  • Introducing interactive data visualisations with R via htmlwidgets and the pipe operator
  • Incorporating text with code and interactive output using RMarkdown
  • Publishing interactive RMarkdown reports to the web
  • Designing interactive applications in R using Shiny
  • Publishing Shiny applications to

Target Audience

R users who want their audiences to interact and explore their data through interactive visualisations. Or those who wish to provide these interactive tools to others to supplement their analysis. Datasets will range from numerical observations, geolocations to colocation network data, and should therefore be interesting to anyone involved with social, physical or medical science, economics or computer science. 

Knowledge Assumed

A working knowledge of R is assumed. For inexperienced users you’re recommended to study the free Intro to R course here:

The RSS also runs a two-day foundation level R course called 'Introduction to R and Regression Modelling in R.' 


Intermediate (some prior knowledge)


£588 - £816 (inc VAT)

Website and registration


Greater London


Qualitative Data Handling and Data Analysis, Python, Interactive Visualisation , RMarkdown , htmlwidgets , Shiny

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