Shiny applications (design and deployment)
Shiny: web applications that runs R
Shiny is a framework used to design web applications in R. At ThinkR, we design custom dashboard and other web interfaces to meet all your needs. This will allow you to share your data and analysis across all departments of your company. If you are a modeler, you will appreciate letting your collaborators interactively define the list of parameters of your models. If you are a scientist, you may wish to set up a creative interface to interact with experts in your field or to collect participatory science data.
For the end user, switching on is simple. A Shiny application can be hosted on a server or installed on the users’ computer (as a package or as an.exe). It allows you to access the R code interactively from RStudio or via a web browser.
Why choose Shiny? To give people who don’t know R access to all the power of R. By designing an interactive web interface that can execute R code in the background, you can provide an ergonomic and user-friendly way to run calculations, present graphics… without having to write a single line of R code. And they can access it directly from their web browser. Look, we’re also talking about Shiny on our blog!
Examples of Shiny applications
You can see examples of small shiny applications on our server at http://shiny.thinkr.fr/ :
- Collage: Transforms a picture into a kitten photo mosaic
- Legislatives: Mapping of the Results of the French Legislative Elections 2017
- Tweetstorm: A dashboard to aggregate tweets exchanged during the useR! 2017 conference.
- Prenoms: A dashboard to visualize the evolution of the popularity of baby names in France since 1900
Use cases implying conception of Shiny applications
- Redesign and optimization of a shiny application
- Shiny running Python models
- Development of hardware failure tracking software
- Audit and redesign of a shiny application
- Creation of a multi-language Shiny Application
- Migration to Shiny of a SAS analysis tool
- SAS code interface via Shiny
- High-density data visualization
- Deployment of a Shiny app for several hundred users
- Building an experimental design tool
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