semantic.dashboard

Dashboard with Semantic UI Support for Shiny

Are you fed up with ordinary shinydashboard look?

Give your app a new life with Semantic UI support. It cannot be any easier! Just install semantic.dashboard and load it instead to your app. Thanks to the compatibility with classical dashboard you don't have to start from scratch.

#########################
library(shinydashboard) # <-- You only need to change this line to: library(semantic.dashboard)
#########################
ui <- dashboardPage(
  dashboardHeader(title = "Basic dashboard"),
  dashboardSidebar(sidebarMenu(
      menuItem(tabName = "home", text = "Home", icon = icon("home")),
      menuItem(tabName = "another", text = "Another Tab", icon = icon("heart"))
  )),
  dashboardBody(
    fluidRow(
      box(plotOutput("plot1", height = 250)),
      box(
        title = "Controls",
        sliderInput("slider", "Number of observations:", 1, 100, 50)
      )
    )
  )
)

server <- function(input, output) {
  set.seed(122)
  histdata <- rnorm(500)
  output$plot1 <- renderPlot({
    data <- histdata[seq_len(input$slider)]
    hist(data)
  })
}

shinyApp(ui, server)

semantic.dashboard offers basic functions for creating dashboard with Semantic UI but not only. You can select from number of Semantic UI Themes and easily adjust the look of your dashboard.

Check more examples below or in the examples folder.

Source code

This library source code can be found on Appsilon Data Science's Github:
https://github.com/Appsilon/semantic.dashboard

How to install?

Install shiny.semantic library first. Here you can find how.

At the moment it's possible to install this library through devtools.

devtools::install_github("Appsilon/semantic.dashboard")

To install previous version you can run:

devtools::install_github("Appsilon/semantic.dashboard", ref = "0.1.0")

Example

More examples are in the examples/ folder from the GitHub repository.

You can also read this tutorial to learn how to build your first semantic.dashboard app.

How to contribute?

If you want to contribute to this project please submit a regular PR, once you're done with new feature or bug fix.

Changes in documentation

Both repository README.md file and an official documentation page are generated with Rmarkdown, so if there is a need to update them, please modify accordingly a README.Rmd file and run a build_readme.R script to compile it.

Troubleshooting

We used the latest versions of dependencies for this library, so please update your R environment before installation.

However, if you encounter any problems, try the following:

1. Up-to-date R language environment
2. Installing specific dependent libraries versions

   • shiny.semantic

     devtools::install_github("Appsilon/shiny.semantic")
     

Future enhacements

• CRAN release

Appsilon Data Science

Get in touch [email protected]