Summary and Setup

This is a new lesson built with The Carpentries Workbench.

R Shiny is a popular R package that allows you to transform complex analytics into powerful, user-friendly interactive visualisation tools.

This lesson is designed to provide an introduction to R Shiny and demonstrate how you can use it to create web apps and more interactive data visualisations. It is derived from the Carpentries Incubator R Shiny Geospatial lesson and rewritten for QCIF delivery.

Prerequisite

Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to ensure the proper setup of tools for an efficient workflow. To most effectively use these materials, please make sure to download the data and install everything before working through this lesson.

R Skill Level

This lesson assumes you have prior knowledge of R and experience with RStudio. If you’ve never used R or RStudio before, or need a refresher, start with R for Reproducible Scientific Analysis.

Data Sets

The csv file used in this lesson lesson was generated from data from an Employment Projection Model: A set of employment forecasts which reflect the Brisbane City Council view of the likely SEQ Regional Employment patterns in the period between 2011 and 2041. They were prepared by the National Institute of Economic and Industrial Research.

We chose two of the datasets “Occupation employment by usual resident employment” and “Industry employment by usual resident employment” and retained only the variables describing region (SA4_Name), suburb (SA2_Name), occupation/industry (Name_2), and projected employment in 2041 (SC2_2041). To create a smaller dataset suitable for teaching, the top three occupations and industries within each region-suburb combination were selected and included in the final dataset.

Software Setup

This lesson assumes you have R and RStudio installed on your computer.