Data Science Assignment

helpers.R

# Note: percent map is designed to work with the counties data set
# It may not work correctly with other data sets if their row order does 
# not exactly match the order in which the maps package plots counties
percent_map <- function(var, color, legend.title, min = 0, max = 100) {

  # generate vector of fill colors for map
  shades <- colorRampPalette(c("white", color))(100)
  
  # constrain gradient to percents that occur between min and max
  var <- pmax(var, min)
  var <- pmin(var, max)
  percents <- as.integer(cut(var, 100, 
    include.lowest = TRUE, ordered = TRUE))
  fills <- shades[percents]

  # plot choropleth map
  map("county", fill = TRUE, col = fills, 
    resolution = 0, lty = 0, projection = "polyconic", 
    myborder = 0, mar = c(0,0,0,0))
  
  # overlay state borders
  map("state", col = "white", fill = FALSE, add = TRUE,
    lty = 1, lwd = 1, projection = "polyconic", 
    myborder = 0, mar = c(0,0,0,0))
  
  # add a legend
  inc <- (max - min) / 4
  legend.text <- c(paste0(min, " % or less"),
    paste0(min + inc, " %"),
    paste0(min + 2 * inc, " %"),
    paste0(min + 3 * inc, " %"),
    paste0(max, " % or more"))
  
  legend("bottomleft", 
    legend = legend.text, 
    fill = shades[c(1, 25, 50, 75, 100)], 
    title = legend.title)
}

getCountyDemo = function(df, select)
{
  switch(select,
         "Percent White" = "white",
         "Percent Black" = "black",
         "Percent Hispanic" = "hispanic",
         "Percent Asian" = "asian")
}

getFilteredVals = function(vect, maxP, minP)
{
  filtVals = vect[vect<maxP]
  filtVals = filtVals[filtVals>minP]
  
  if(all(is.na(filtVals)))
  {
    c(0,0)
  }
  
  filtVals
}

server.R

library(shiny)
library(maps)
library(mapproj)
source("helpers.R")

function(input, output) {
  counties = readRDS("data/counties.rds")

  output$map <- renderPlot({
    cols = getCountyDemo(counties, input$var)
    vals = counties[[cols]]
    filtVals = getFilteredVals(vals, input$range[2], input$range[1])
    percent_map(filtVals, "darkgreen", "Legend")
  })
}

ui.R

library(shiny)

# Define UI for application that draws a histogram
fluidPage(
  
  # Application title
  titlePanel("censusVis"),
  
  # Sidebar with a slider input for the number of bins
  sidebarLayout(
    sidebarPanel(
      helpText("Create demographic maps with info from
               the 2010 US Census."),
      
      selectInput("var",
                  label = "Choose a variable to display",
                  choices = c("Percent White", "Percent Black",
                              "Percent Hispanic", "Percent Asian"),
                  selected = "Percent White"),
      
      sliderInput("range",
                  "Range of interests",
                  min = 0,
                  max = 100,
                  value = c(0, 100))
    ),
    
    # Show a plot of the generated distribution
    mainPanel(
      plotOutput("map")
    )
  )
)