Description

Easy web applications in R

Shiny is an open source R package that provides an elegant and powerful web framework for building web applications using R. Shiny helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

 

Want to build your own Shiny apps?

Interact. Analyze. Communicate.

Take a fresh, interactive approach to telling your data story with Shiny. Let users interact with your data and your analysis. And do it all with R.

 

Shiny is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards. You can also extend your Shiny apps with CSS themes, htmlwidgets, and JavaScript actions.

 

Here is a Shiny app

Shiny apps are easy to write. No web development skills are required.

Google Trend Index

The Google Travel Index tracks queries related to airlines, hotels, beach, southwest, las vegas, flights, etc. The index is set to 1.0 on January 1, 2004 and is calculated only for US search traffic.

 

Description

Shiny comes with a variety of built in input widgets. With minimal syntax it is possible to include widgets like the ones shown on the left in your apps:

# Select type of trend to plot

selectInput(inputId = “type”, label = strong(“Trend index”),

            choices = unique(trend_data$type),

            selected = “Travel”)

 

# Select date range to be plotted

dateRangeInput(“date”, strong(“Date range”),

               start = “2007-01-01”, end = “2017-07-31”,

               min = “2007-01-01”, max = “2017-07-31”)

Displaying outputs is equally hassle-free:

 

mainPanel(

  plotOutput(outputId = “lineplot”, height = “300px”),

  textOutput(outputId = “desc”),

  tags$a(href = “https://www.google.com/finance/domestic_trends”,

         “Source: Google Domestic Trends”, target = “_blank”)

)

                 

Build your plots or tables as you normally would in R, and make them reactive with a call to the appropriate render function:

 

  output$lineplot <- renderPlot({

    plot(x = selected_trends()$date, y = selected_trends()$close, type = “l”,

         xlab = “Date”, ylab = “Trend index”)

  })

                 

Want to find out how we built the Google Trend Index app shown on the left? See the next tab for the complete source code.

 

app.R

# Load packages

library(shiny)

library(shinythemes)

library(dplyr)

library(readr)

 

# Load data

trend_data <- read_csv(“data/trend_data.csv”)

trend_description <- read_csv(“data/trend_description.csv”)

 

# Define UI

ui <- fluidPage(theme = shinytheme(“lumen”),

  titlePanel(“Google Trend Index”),

  sidebarLayout(

    sidebarPanel(

 

      # Select type of trend to plot

      selectInput(inputId = “type”, label = strong(“Trend index”),

                  choices = unique(trend_data$type),

                  selected = “Travel”),

 

      # Select date range to be plotted

      dateRangeInput(“date”, strong(“Date range”), start = “2007-01-01”, end = “2017-07-31”,

                     min = “2007-01-01”, max = “2017-07-31”),

 

      # Select whether to overlay smooth trend line

      checkboxInput(inputId = “smoother”, label = strong(“Overlay smooth trend line”), value = FALSE),

 

      # Display only if the smoother is checked

      conditionalPanel(condition = “input.smoother == true”,

                       sliderInput(inputId = “f”, label = “Smoother span:”,

                                   min = 0.01, max = 1, value = 0.67, step = 0.01,

                                   animate = animationOptions(interval = 100)),

                       HTML(“Higher values give more smoothness.”)

      )

    ),

 

    # Output: Description, lineplot, and reference

    mainPanel(

      plotOutput(outputId = “lineplot”, height = “300px”),

      textOutput(outputId = “desc”),

      tags$a(href = “https://www.google.com/finance/domestic_trends”, “Source: Google Domestic Trends”, target = “_blank”)

    )

  )

)

 

# Define server function

server <- function(input, output) {

 

  # Subset data

  selected_trends <- reactive({

    req(input$date)

    validate(need(!is.na(input$date[1]) & !is.na(input$date[2]), “Error: Please provide both a start and an end date.”))

    validate(need(input$date[1] < input$date[2], “Error: Start date should be earlier than end date.”))

    trend_data %>%

      filter(

        type == input$type,

        date > as.POSIXct(input$date[1]) & date < as.POSIXct(input$date[2]

        ))

  })

 

 

  # Create scatterplot object the plotOutput function is expecting

  output$lineplot <- renderPlot({

    color = “#434343”

    par(mar = c(4, 4, 1, 1))

    plot(x = selected_trends()$date, y = selected_trends()$close, type = “l”,

         xlab = “Date”, ylab = “Trend index”, col = color, fg = color, col.lab = color, col.axis = color)

    # Display only if smoother is checked

    if(input$smoother){

      smooth_curve <- lowess(x = as.numeric(selected_trends()$date), y = selected_trends()$close, f = input$f)

      lines(smooth_curve, col = “#E6553A”, lwd = 3)

    }

  })

 

  # Pull in description of trend

  output$desc <- renderText({

    trend_text <- filter(trend_description, type == input$type) %>% pull(text)

    paste(trend_text, “The index is set to 1.0 on January 1, 2004 and is calculated only for US search traffic.”)

  })

}

 

# Create Shiny object

shinyApp(ui = ui, server = server)

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