revenue_shiny.R

library(shiny)
library(shinydashboard)
library(ggplot2)
library(dplyr)

recommendation <- read.csv('recommendation.csv', stringsAsFactors = FALSE, header = TRUE)
head(recommendation)

#Dashboard header carrying the title of the dashboard
header <- dashboardHeader(title = "Basic Dashboard")

#Sidebar content of the dashboard
sidebar <- dashboardSidebar(
  sidebarMenu(
    menuItem("Dashboard", tabName = "dashboard", icon = icon("dashboard")),
    menuItem("Visit-us", icon = icon("send", lib = 'glyphicon'),
             href = "http://www.suebayes.com")
  )
)

frow1 <- fluidRow(
  valueBoxOutput("value1"),
  valueBoxOutput("value2"),
  valueBoxOutput("value3")
)
frow2 <- fluidRow(
  box(
    title = "Revenue per Account",
    status = "primary",
    solidHeader = TRUE,
    collapsible = TRUE,
    plotOutput("revenuebyPrd", height = "300px")
  ),
  box(
    title = "Revenue per Product",
    status = "primary",
    solidHeader = TRUE,
    collapsible = TRUE,
    plotOutput("revenuebyRegion", height = "300px")
  )
  
)

body <- dashboardBody(frow1, frow2)

ui <- dashboardPage(
  title = "Sue Bayes Dashboard Example", header, sidebar, body, skin = "red")

#create the server functions for the dashboard
server <- function(input, output) {
  #some data manipulation to dervie the values of the KPI boxes
  
  total.revenue <-  sum(recommendation$Revenue)
  sales.account <- recommendation %>% 
    group_by(Account) %>% 
    summarise(value = sum(Revenue)) %>% 
    filter(value == max(value))
  prof.prod <- recommendation %>% group_by(Product) %>% 
    summarise(value = sum(Revenue)) %>% 
    filter(value==max(value))
  
  #creating the valueBoxOutput content
  
  output$value1 <- renderValueBox({
    valueBox(
      formatC(sales.account$value, format="d", big.mark = ','),
      paste('Top Account: ', sales.account$Account),
      icon = icon("stats", lib = 'glyphicon'),
      color = 'purple')
})
  
  output$value2 <- renderValueBox({
    valueBox(
      formatC(total.revenue, format="d", big.mark = ','),
      paste('Top Expected Revenue '),
      icon = icon("stats", lib = 'glyphicon'),
      color = 'green')
  })
  
  output$value3 <- renderValueBox({
    valueBox(
      formatC(prof.prod$value, format="d", big.mark = ','),
      paste('Top Product: ', prof.prod$Product),
      icon = icon("stats", lib = 'glyphicon'),
      color = 'yellow')
  })

#creating the plotOutput content
  output$revenuebyPrd <- renderPlot({
    ggplot(data = recommendation,
           aes(x=Product, y=Revenue, fill=factor(Region))) +
      geom_bar(position = "dodge", stat = "identity") +
      ylab("Revenue (in £s)") +
      xlab("Product") + theme(legend.position="bottom" 
                              ,plot.title = element_text(size=15, face="bold")) + 
      ggtitle("Revenue by Product") + labs(fill = "Region")
  })
  output$revenuebyRegion <- renderPlot({
    ggplot(data = recommendation, 
           aes(x=Account, y=Revenue, fill=factor(Region))) + 
      geom_bar(position = "dodge", stat = "identity") + ylab("Revenue (in Euros)") + 
      xlab("Account") + theme(legend.position="bottom" 
                              ,plot.title = element_text(size=15, face="bold")) + 
      ggtitle("Revenue by Region") + labs(fill = "Region")
  })
    
}

shinyApp(ui, server)