Illustration

global.R

#initialize
library(ggplot2) 

TestData <- data.frame(   a = rep(LETTERS[1:4],10),
                          b = rep(c('A','B'),20),
                          c = rep(LETTERS[1:5],each=8),
                          d = rep(c('A','B'),2,each=10),
                          m1 = rnorm(40),
                          m2 = rnorm(40),
                          m3 = rnorm(40),
                          m4 = rnorm(40),
                          m5 = rnorm(40),
                          x  = rep(1:5,each=8)
)

#helper function (convert vector to named list)
namel<-function (vec){
     tmp<-as.list(vec)
     names(tmp)<-as.character(unlist(vec))
     tmp
}

# Function to aggregate data based on selected columns (Source Columns)
AggregateData <- function(data,Columns=NA) {

     require(sqldf)
     if (all(is.na(Columns))) {
          sql <- "select 
                    sum(m1) as m1, sum(m2) as m2, sum(m3) as m3, sum(m4) as m4, sum(m5) as m5, x
                 from TestData group by x" 
          sqldf(sql)                
     } else {
          sql <- paste("select ", paste(Columns, collapse =','), ",
                    sum(m1) as m1, sum(m2) as m2, sum(m3) as m3, sum(m4) as m4, sum(m5) as m5, x
                 from TestData group by ",paste(Columns, collapse =','),", x")
          sqldf(sql)          
     }
}

# Function to plot data
PlotData <- function(data,x="x",y="m1") { 
     ggplot(data, aes_string(x=x, y=y)) + geom_line()
}

server.R

# shiny server side code for each call
shinyServer(function(input, output, session){
     #update variable and group based on dataset
     observe({
          
          require(sqldf)
          
          if (is.null(input$source_columns)) {
               obj <-TestData
          } else {
               obj<-AggregateData(TestData,Columns=input$source_columns)
          }
          
          var.opts<-namel(colnames(obj))
          var.opts.original.slicers <- namel(colnames(TestData))           
          measures <- c('m1','m2','m3','m4','m5')
           
          var.opts.slicers <- var.opts[!(var.opts %in% c(measures,'x'))]
          var.opts.original.slicers <- var.opts.original.slicers[!(var.opts.original.slicers %in% c(measures,'x'))]
          var.opts.measures <- var.opts[var.opts %in% measures]
          
          updateSelectInput(session, "source_columns", choices = var.opts.original.slicers, selected=var.opts.slicers)
          updateSelectInput(session, "xaxis", choices = var.opts.slicers,selected="x")
          updateSelectInput(session, "yaxis", choices = var.opts.measures,selected="m1")
          
     })
     
     output$plot <- renderUI({
          plotOutput("p")
     })
     
     #plotting function using ggplot2
     
     output$p <- renderPlot({
          require(ggplot2)
          obj <- AggregateData(TestData,Columns=input$source_columns)
          p <- PlotData(obj,x=input$xaxis, y=input$yaxis)
          print(p)
     })     
})

ui.R

shinyUI(pageWithSidebar(
     # title
     headerPanel("Analysis setup"),
     
     #input
     sidebarPanel
     (
          selectInput("source_columns","Source Columns:", "Loading...",multiple=TRUE),
          selectInput("xaxis","X Axis:", "Loading..."),
          selectInput("yaxis","Y Axis:", "Loading...")
     ),     
     
     # output				
     mainPanel(
          #h3('Vintage Analysis'),
          uiOutput("plot") # depends on input 
     )
))