Learn more about the best R Shiny dashboards
Are you looking for an easy and effective way to build apps that consist of reactive elements, easily changed with user inputs? Do you want to combine large data with unique storytelling experiences and captivate your audiences? Thanks to the R Shiny dashboard, you can achieve all of that and more! Let’s learn more about the dashboards that will make the biggest difference.
Benefits of implementing R Shiny dashboards
Why are R Shiny dashboards a great choice? Well – for one – this solution is based on R, which also means that it has all the same statistical and machine learning capabilities. Another benefit is reactivity – every element of your dashboard can be coded to respond to user inputs. Styling is definitely not a problem, and with Shiny, you can implement virtually any custom design you want. What is crucial, all of that can be achieved in minimal time – you will need only about a month to go from rough sketches to advanced dashboard getting completed. Sounds good, right?
Discover examples of popular dashboards
R Shiny offers plenty of excellent dashboards, but we don’t have the space to introduce them all here. However, we can give you some of the most intriguing examples to check out!
The Port Analytics dashboard, as its name suggests, provides a comprehensive overview of port logistics. It can be used to support dock managers as it shows such crucial information as the current number of vessels as well as the number of ships in a port at selected periods of time. Of course, all of that data is presented in a highly engaging way, using charts, maps, and plots. And because of reactivity, user selection can influence the data table showcased by this R Shiny dashboard.
Shiny Enterprise App
Shiny Enterprise App is a prime example of how quickly a dashboard may be created. You can build your own design in no time and use such crucial metrics as Revenue, Costs, Active Users, and Complaints. Sales revenue and breakdown of all the essential data are showcased visually in a highly engaging way.
Building Damage Assessment
This dashboard is yet another example of combining data analytics and AI to develop admiringly helpful solutions. The Damage Assessment app can be used in areas that have been struck by natural disasters such as earthquakes, fires, or floods. With the aid of satellite imagery, the AI can identify which buildings have been impacted by the elements. The dashboard then highlights structures in corresponding colors – red for destroyed, orange for majorly damaged, yellow for slightly damaged, and green for no damages.
The Visualise dashboard, focused on visualizing disaster risk, can help to save lives. It aggregates nationwide household survey data with hazard modeling. It works at national, provincial, and household levels and shows which areas will be vulnerable to cyclone threat.
Interested? Check out other R Shiny dashboards that can help you with fast prototyping, full-stack development, and visualizations.