server.R

library(shiny)
library(ggvis)
colors <- c('black','red','blue','green')
shinyServer(function(input, output, session) {
		dsR <- reactive({
			invalidateLater(input$refresh, session);
			data.frame(Value = rnorm(n = input$nObs, mean = input$mean, sd = input$sd))	
		})
		
		gv <- reactive({
			ggvis(dsR,props(x = ~Value,
					     fillOpacity := input_slider(0, 1, .8, step = .1, label = "Opacity")),
			      #This will cause the mark_{rect,path} to be reset to black on every refresh
#			      transform_bin(binwidth = (max(dsR()) - min(dsR())) / input$nBars)) + 
				#This works fine
			      transform_bin()) +
				mark_rect(props(x = ~xmin__, x2 = ~xmax__, y = ~count__, y2 = 0,
						fill := input_select(choices = colors, 
								    selected = 'black',
								    multiple = FALSE,
								    label = 'Bar fill color'))) + 
				mark_path(props(x = ~x, y = ~count__,
						fill := input_select(choices = colors,
								     selected = 'black',
								     multiple = FALSE,
								     label = 'Path fill color'))) + 
				dscale('x',type = 'numeric', domain = c(-500,500)) + 
				guide_axis('x',title = 'X value (binned)') + guide_axis('y',title = 'Frequency') 
			
		})
		
		output$distPlot <- observe_ggvis(gv,plot_id = 'distPlot',session = session)
		output$distPlotC <- renderControls(gv)
})

ui.R

library(shiny)
library(ggvis)

shinyUI(pageWithSidebar(
  
  # Application title
  headerPanel("The effect of sample size and variance."),
  
  # Sidebar with a slider input for number of observations
  sidebarPanel(
    sliderInput("nObs",
                "Number of observations:",
                min = 5,
                max = 10000,
                value = 20),
    sliderInput("sd",
     "Standard Deviation:",
     min = .01,
     max = 500,
     value = 1,
     step = .01),
    sliderInput('mean',
     'Mean:',
     min = -100,
     max = 100,
     value = 0),
    numericInput('refresh',
     'Refresh Rate (in ms)',
     3000,
     500,
     60000),
    numericInput('nBars',
     "Number of bars",
     30,
     1,
     1000)
  ),
  
  
  # Show a plot of the generated distribution
  mainPanel(
    ggvis_output("distPlot"),
    ggvisControlOutput('distPlotC')
  )
))