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server.R
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server.R
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####################################
#### Google Analytics - server.R ###
####################################
library(shiny)
library(plyr)
library(ggplot2)
load("analytics.Rdata") # load the dataframe
# test - are they using the older version of Shiny?
packageCheck = unlist(packageVersion("shiny"))
if(packageCheck[1] == 0 & packageCheck[2] < 9){
shinyOld = TRUE
} else {
shinyOld = FALSE
}
shinyServer(function(input, output, session){ # pass in a session argument
# for extra functionality
# keep control of the checkbox control
observe({
if(class(input$domainShow) != "character"){
updateCheckboxGroupInput(session, "domainShow",
choices = list("NHS users" = "NHS",
"Other" = "Other"),
selected = ifelse(shinyOld, "NHS users", "NHS")
)
}
})
# handle reactive UI
output$reacDomains <- renderUI({
domainList = unique(as.character(passData()$networkDomain))
selectInput("subDomains", "Choose subdomain", domainList)
})
# handle custom URL
observe({
searchString <- parseQueryString(session$clientData$url_search)
if(length(searchString)>0){
## deal with first query which indicates the audience
if(searchString[[1]] == "nhs"){
updateCheckboxGroupInput(session, "domainShow",
choices = list("NHS users" = "NHS",
"Other" = "Other"),
selected = "NHS")
updateRadioButtons(session, "outputType",
choices = list("Visitors" = "visitors",
"Bounce rate" = "bounceRate",
"Time on site" = "timeOnSite"),
selected= "Bounce rate")
updateTabsetPanel(session, inputId = "theTabs", selected = "summary")
}
if(searchString[[1]] == "other"){
updateCheckboxGroupInput(session, "domainShow",
choices = list("NHS users" = "NHS",
"Other" = "Other"),
selected = c("NHS users", "Other"))
updateRadioButtons(session, "outputType",
choices = list("Visitors" = "visitors",
"Bounce rate" = "bounceRate",
"Time on site" = "timeOnSite"),
selected= "Visitors")
updateTabsetPanel(session, inputId = "theTabs", selected = "monthly")
}
## do they want a smooth?
if(searchString[[2]] == "yes"){
updateCheckboxInput(session, inputId = "smoother",
value = TRUE)
}
}
})
# prep data once and then pass around the program
passData <- reactive({
if(input$theTabs != "hourly"){
analytics <- analytics[analytics$Date %in% seq.Date(input$dateRange[1], input$dateRange[2], by = "days"),]
}
if(input$theTabs != "monthly"){
analytics <- analytics[analytics$Hour %in% as.numeric(input$minimumTime) : as.numeric(input$maximumTime),]
}
analytics <- analytics[analytics$Domain %in% unlist(input$domainShow),]
analytics
})
output$monthGraph <- renderPlot({
graphData <- ddply(passData(), .(Domain, Date), numcolwise(sum))
if(input$outputType == "visitors"){
theGraph <- ggplot(graphData, aes(x = Date, y = visitors, group = Domain, colour = Domain)) + geom_line() +
ylab("Unique visitors")
}
if(input$outputType == "bounceRate"){
theGraph <- ggplot(graphData, aes(x = Date, y = bounces / visits * 100, group = Domain, colour = Domain)) +
geom_line() + ylab("Bounce rate %")
}
if(input$outputType == "timeOnSite"){
theGraph <- ggplot(graphData, aes(x = Date, y = timeOnSite / visits, group = Domain, colour = Domain)) +
geom_line() + ylab("Average time on site")
}
if(input$smoother){
theGraph <- theGraph + geom_smooth(method = input$linearModel)
}
print(theGraph)
})
output$animateGraph <- renderPlot({
graphData <- ddply(passData(), .(Domain, Date), numcolwise(sum))
if(input$outputType == "visitors"){
theGraph <- ggplot(graphData, aes(x = Date, y = visitors, group = Domain, colour = Domain)) + geom_line() +
ylab("Unique visitors")
}
if(input$outputType == "bounceRate"){
theGraph <- ggplot(graphData, aes(x = Date, y = bounces / visits * 100, group = Domain, colour = Domain)) +
geom_line() + ylab("Bounce rate %")
}
if(input$outputType == "timeOnSite"){
theGraph <- ggplot(graphData, aes(x = Date, y = timeOnSite / visits, group = Domain, colour = Domain)) +
geom_line() + ylab("Average time on site")
}
smoothData = graphData[graphData$Date %in%
quantile(graphData$Date, input$animation/100, type=1):
quantile(graphData$Date,
(input$animation+20)/100, type=1),]
theGraph <- theGraph + geom_smooth(data = smoothData, method = "lm",
colour = "black")
print(theGraph)
})
output$hourGraph <- renderPlot({
graphData = ddply(passData(), .(Domain, Hour), numcolwise(sum))
if(input$outputType == "visitors"){
theGraph <- ggplot(graphData, aes(x = Hour, y = visitors, group = Domain, colour = Domain)) + geom_line() +
ylab("Unique visitors")
}
if(input$outputType == "bounceRate"){
theGraph <- ggplot(graphData, aes(x = Hour, y = bounces / visits * 100, group = Domain, colour = Domain)) +
geom_line() + ylab("Bounce rate %")
}
if(input$outputType == "timeOnSite"){
theGraph <- ggplot(graphData, aes(x = Hour, y = timeOnSite / visits, group = Domain, colour = Domain)) +
geom_line() + ylab("Average time on site")
}
if(input$smoother){
theGraph <- theGraph + geom_smooth(method = "loess")
}
print(theGraph)
})
output$textDisplay <- renderText({
if(is.null(input$dateRange)) return()
paste(
length(seq.Date(input$dateRange[1], input$dateRange[2], by = "days")),
" days are summarised. There were", sum(passData()$visitors),
"visitors in this time period."
)
})
### following sections define the code that makes graphs downloadable
myTrend <- reactive({
graphData <- ddply(passData(), .(Domain, Date), numcolwise(sum))
if(input$outputType == "visitors"){
theGraph <- ggplot(graphData, aes(x = Date, y = visitors, group = Domain, colour = Domain)) + geom_line() +
ylab("Unique visitors")
}
if(input$outputType == "bounceRate"){
theGraph <- ggplot(graphData, aes(x = Date, y = bounces / visits * 100, group = Domain, colour = Domain)) +
geom_line() + ylab("Bounce rate %")
}
if(input$outputType == "timeOnSite"){
theGraph <- ggplot(graphData, aes(x = Date, y = timeOnSite / visits, group = Domain, colour = Domain)) +
geom_line() + ylab("Average time on site")
}
if(input$smoother){
theGraph <- theGraph + geom_smooth(method = input$linearModel)
}
print(theGraph)
})
output$downloadData.trend <- downloadHandler(
filename <- function() {
paste("Trend_plot", Sys.Date(),".png",sep="") },
content <- function(file) {
png(file, width = 980, height = 400,
units = "px", pointsize = 12,
bg = "white", res = NA)
trend.plot <- myTrend()
print(trend.plot)
dev.off()},
contentType = 'image/png')
})