Cacher is the code snippet organizer for pro developers

library(shiny)

shinyUI(fluidPage(
  titlePanel("stockVis"),
  
  sidebarLayout(
    sidebarPanel(
      helpText("Select a stock to examine. 
        Information will be collected from yahoo finance."),
    
      textInput("symb", "Symbol", "SPY"),
    
      dateRangeInput("dates", 
        "Date range",
        start = "2013-01-01", 
        end = as.character(Sys.Date())),
   
      actionButton("get", "Get Stock"),
      
      br(),
      br(),
      
      checkboxInput("log", "Plot y axis on log scale", 
        value = FALSE),
      
      checkboxInput("adjust", 
        "Adjust prices for inflation", value = FALSE)
    ),
    
    mainPanel(plotOutput("plot"))
  )
))

# server.R

library(quantmod)
source("helpers.R")


shinyServer(function(input, output) {
  
  dataInput <- reactive({  
    getSymbols(input$symb, src = "yahoo", 
               from = input$dates[1],
               to = input$dates[2],
               auto.assign = FALSE)
  })
  
  finalInput <- reactive({
    if (!input$adjust) return(dataInput())
    adjust(dataInput())
  })
  
  output$plot <- renderPlot({
    chartSeries(finalInput(), theme = chartTheme("white"), 
                type = "line", log.scale = input$log, TA = NULL)
  })
})

if (!exists(".inflation")) {
  .inflation <- getSymbols('CPIAUCNS', src = 'FRED', 
     auto.assign = FALSE)
}  

# adjusts yahoo finance data with the monthly consumer price index 
# values provided by the Federal Reserve of St. Louis
# historical prices are returned in present values 
adjust <- function(data) {

      latestcpi <- last(.inflation)[[1]]
      inf.latest <- time(last(.inflation))
      months <- split(data)               
      
      adjust_month <- function(month) {               
        date <- substr(min(time(month[1]), inf.latest), 1, 7)
        coredata(month) * latestcpi / .inflation[date][[1]]
      }
      
      adjs <- lapply(months, adjust_month)
      adj <- do.call("rbind", adjs)
      axts <- xts(adj, order.by = time(data))
      axts[ , 5] <- Vo(data)
      axts
}