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.
Shiny combines the computational power of R with the interactivity of the modern web.
Here is a Shiny app
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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$type),
selected = "Travel")
# Select date range to be plotted
dateRangeInput("date", strong("Date range"),
start = "2007-01-01", end = "2017-07-31",
min = "2007-01-01", max = "2017-07-31")
mainPanel(
plotOutput(outputId = "lineplot", height = "300px"),
textOutput(outputId = "desc"),
tags$a(href = "http://www.google.com/finance/domestic_trends",
"Source: Google Domestic Trends", target = "_blank")
)
output$lineplot <- renderPlot({
plot(x = selected_trends()$date, y = selected_trends()$close, type = "l",
xlab = "Date", ylab = "Trend index")
})
# Load packages
library(shiny)
library(shinythemes)
library(dplyr)
library(readr)
# Load data
trend_data <- read_csv("data/trend_data.csv")
trend_description <- read_csv("data/trend_description.csv")
# Define UI
ui <- fluidPage(theme = shinytheme("lumen"),
titlePanel("Google Trend Index"),
sidebarLayout(
sidebarPanel(
# Select type of trend to plot
selectInput(inputId = "type", label = strong("Trend index"),
choices = unique(trend_data$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$a(href = "http://www.google.com/finance/domestic_trends", "Source: Google Domestic Trends", target = "_blank")
)
)
)
# Define server function
server <- function(input, output) {
# Subset data
selected_trends <- reactive({
req(input$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)
Hosting and Deployment
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