To smooth the process of creating visually striking Shiny UI’s and robust applications, Appsilon is working on designing Cheatsheets for our Shiny packages. The first of these in the Cheatsheet series is the shiny.semantic package. The Cheatsheet will introduce you to shiny.semantic and methods for bringing Semantic UI in R and Shiny. With the shiny.semantic Cheatsheet, you can catch a quick glimpse into the package basics and jump right into its use.
- shiny.semantic Cheatsheet
- Shiny app benefits with Semantic UI in R
- Appsilon’s open source: more than Semantic UI in R
The shiny.semantic package is a Fomantic UI wrapper for Shiny. The R/Shiny package allows you to add the powerful UI library Semantic UI in R. Use shiny.semantic to simplify your UI by reducing the amount of code needed to produce impressive, interactive Shiny dashboards in minutes. Make creating quality Shiny UIs a hassle-free experience with shiny.semantic.
Enhance your Shiny application from functionality to beautiful UIs with Appsilon’s open source packages.
Shiny app benefits with Semantic UI in R
The two images below showcase the difference a few lines of code can make to an R Shiny dashboard. The first image is the UI for the Utah Department of Environmental Quality’s Water Quality dashboard built using
shinydashboard. The data plots and tools have potential, but the presentation leaves much to be desired. The UI is a bit cluttered and isn’t immediately intuitive.
R is a powerful tool for data science. Learn why you should be using R Shiny for enterprise application development.
And so the search began for a simple, yet effective solution:
shiny.semantic. With just a few Semantic UI components, the dashboard is transformed into something clean and easy to navigate. Using shiny.semantic the simple, yet effective Shiny dashboard was upgraded to an aesthetically pleasing one and in a quick, reproducible manner.
Appsilon’s open source: more than Semantic UI in R
Appsilon prides itself on its contributions to R and the open-source community at large. Our team has built several open source packages and Shiny tools to improve the Shiny development process. We know the value R has as a powerful language for data science, but we understand the level of complexity it brings when developing applications. That’s why we want the R community to have access to our experience and knowledge to help grow the R/Shiny ecosystem. We encourage you to visit the Appsilon Github and discover new ways to improve your data science applications. If you find a package useful, consider dropping a star. And if you see areas for improvement please send a pull request or start a conversation in the repo’s discussion.
If you’re in need of a quick solution, the Appsilon team has recently launched several open source Shiny dashboard templates. You can download the templates for free! Simply download, customize components and branding, and launch! As the global experts in R/Shiny, we at Appsilon want to push the boundaries of what’s possible with R/Shiny. And should you need assistance with your enterprise Shiny application, reach out to us. We love solving data science problems.