Understanding restriction of range with Shiny!

I made this: emilkirkegaard.shinyapps.io/Understanding_restriction_of_range/

Source:

# ui.R
shinyUI(fluidPage(
  titlePanel(title, windowTitle = title),
  
  sidebarLayout(
    sidebarPanel(
      helpText("Get an intuitive understanding of restriction of range using this interactive plot. The slider below limits the dataset to those within the limits."),
      
      sliderInput("limits",
        label = "Restriction of range",
        min = -5, max = 5, value = c(-5, 5), step=.1),
      
      helpText("Note that these are Z-values. A Z-value of +/- 2 corresponds to the 98th or 2th centile, respectively.")
      ),
    
    
    mainPanel(
      plotOutput("plot"),width=8,
      
      textOutput("text")
      )
  )
))
# server.R
shinyServer(
  function(input, output) {
    output$plot <- renderPlot({
      #limits
      lower.limit = input$limits[1] #lower limit
      upper.limit = input$limits[2]  #upper limit
      
      #adjust data object
      data["X.restricted"] = data["X"] #copy X
      data[data[,1]<lower.limit | data[,1]>upper.limit,"X.restricted"] = NA #remove values
      group = data.frame(rep("Included",nrow(data))) #create group var
      colnames(group) = "group" #rename
      levels(group$group) = c("Included","Excluded") #add second factor level
      group[is.na(data["X.restricted"])] = "Excluded" #is NA?
      data["group"] = group #add to data
      
      #plot
      xyplot(Y ~ X, data, type=c("p","r"), col.line = "darkorange", lwd = 1,
             group=group, auto.key = TRUE)
    })
    
    output$text <- renderPrint({
      #limits
      lower.limit = input$limits[1] #lower limit
      upper.limit = input$limits[2]  #upper limit
      
      #adjust data object
      data["X.restricted"] = data["X"] #copy X
      data[data[,1]<lower.limit | data[,1]>upper.limit,"X.restricted"] = NA #remove values
      group = data.frame(rep("Included",nrow(data))) #create group var
      colnames(group) = "group" #rename
      levels(group$group) = c("Included","Excluded") #add second factor level
      group[is.na(data["X.restricted"])] = "Excluded" #is NA?
      data["group"] = group #add to data
      
      #correlations
      cors = cor(data[1:3], use="pairwise")
      r = round(cors[3,2],2)
      #print output
      str = paste0("The correlation in the full dataset is .50, the correlation in the restricted dataset is ",r)
      print(str)
    })
    
  }
)
#global.R
library("lattice")
data = read.csv("data.csv",row.names = 1) #load data
title = "Understanding restriction of range"
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