Bootstraplib’s Documentation Demo

This not only can help you in beautifying the looks of your Shiny app / RMarkdown but also can open up multiple arenas to create Organziation-theme specific reports from RMarkdown and dashboards from Shiny, Thus making Organiztions embrace reproducible reports/apps than the never-die Powerpoint.

If you’re interested in learning more about Shiny, Check out THIS

Sample Shiny Code with Bootstraplib Live Theme Editor

ui.R

#
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)

bs_theme_new(bootswatch = "sketchy")


bs_theme_add_variables(`body-bg` = "#2CEC11")
bs_theme_add_variables(`body-bg` = "#2CEC11", `body-color` = "#292123")
bs_theme_add_variables(`body-bg` = "#2CEC11", `body-color` = "#F61D49")
# Define UI for application that draws a histogram
shinyUI(fluidPage(
    bootstrap(),
    

    # Application title
    titlePanel("Old Faithful Geyser Data"),

    # Sidebar with a slider input for number of bins
    sidebarLayout(
        sidebarPanel(
            sliderInput("bins",
                        "Number of bins:",
                        min = 1,
                        max = 50,
                        value = 30)
        ),

        # Show a plot of the generated distribution
        mainPanel(
            plotOutput("distPlot")
        )
    )
))

server.R

#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)
library(bootstraplib)



# Define server logic required to draw a histogram
shinyServer(function(input, output) {
    # uncomment this when you want live previewing / editing of this theme    
    #bootstraplib::bs_themer()
    output$distPlot <- renderPlot({

        # generate bins based on input$bins from ui.R
        x    <- faithful[, 2]
        bins <- seq(min(x), max(x), length.out = input$bins + 1)

        # draw the histogram with the specified number of bins
        hist(x, breaks = bins, col = 'darkgray', border = 'white')

    })

})