How to Improve R Shiny’s Design
It doesn’t take a lot to make a Shiny application look better.
One R package that make clean designs easy is Appsilon’s shiny.semantic package. This package uses the Fomantic-UI framework (previously named “semantic”).
shiny.semantic’s grids, columns, and segments can quickly organize content in a way that’s simple and clean.
Watch the video below to see how to use these resources to improve a standard Shiny application’s design. The tutorial’s code is available here.
An early client of Free State Analytics wanted to develop an application to help with autism spectrum diagnosis.
The product, if successful, would be used in clinics and school settings across North America.
Since the primary users would be clinicians or school psychologists, it was important that the application made the statistical methodology more accessible through clean design. shiny.semantic was an ideal framework for this reason.
You can learn more about our work on this project here.
Why Good Design in R Shiny Matters?
Good design is important in R Shiny development, although it’s often neglected.
Shiny’s “functionality over form” has kept it from wider adoption in the business community.
Business users expect insights to be communicated with clarity, but many Shiny applications are not designed with this in mind.
Tableau and PowerBI dashboards, however, are designed to communicate with this audience.
For this reason, I believe improving R Shiny’s aesthetics will make R programmers more competitive in business analytics.
References and Credits
Special thanks to Adam Santone for providing an old R Shiny application for me to use for this tutorial.
Song credits provided by Pixabay.