在Shiny App中需要加载数据、R脚本和包。
# #数据
counties.rds
是美国每个州的人口数据集，收集在R 包
UScensus2010
，也可以直接下载：
here
.
counties.rds数据：
每个州的名字
每个州的总人口
每个州居民中白人、黑人、西班牙裔或亚裔的百分比
如果当前要创建一个census-app Shiny app
在census-app下创建一个data文件夹，放置数据
counties <- readRDS("census-app/data/counties.rds")
head(counties)
name total.pop white black hispanic asian
1 alabama,autauga 54571 77.2 19.3 2.4 0.9
2 alabama,baldwin 182265 83.5 10.9 4.4 0.7
3 alabama,barbour 27457 46.8 47.8 5.1 0.4
4 alabama,bibb 22915 75.0 22.9 1.8 0.1
5 alabama,blount 57322 88.9 2.5 8.1 0.2
6 alabama,bullock 10914 21.9 71.0 7.1 0.2
#helpers.R
helpers.R可以绘制一个人口分布地图，使用颜色展示人口的变化。
# 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)
helpers.R下载：here
helpers.R中需要调用 maps 和mapprojR 包。
install.packages(c("maps", "mapproj"))
helpers.R中有一个percent_map函数，参数如下：
Argument
Input
library(mapproj)
source("census-app/helpers.R")
counties <- readRDS("census-app/data/counties.rds")
percent_map(counties$white, "darkgreen", "% White")
counties <- readRDS("census-app/data/counties.rds")
percent_map(counties$white, "darkgreen", "% White")
注：在运行server.R，默认的工作路径是server.R保存的位置，所以上面运行source("helpers.R")也可以
第一次调用runApp时，Shiny会运行整个脚本。
当启动应用时，shinyApp函数会运行一次
每当用户访问应用程序时，server就会运行一次
render*函数内的R表达式会运行很多次。每当用户更改小部件的值时，Shiny就会运行它们一次。
这些信息对构建程序有很大的帮助：
运行R脚本、加载库和读取数据集在app.R中的位置应该是在server外，Shiny将只运行这段代码一次。
定义与用户特定的对象在server中，应该在render*外。
render中代码运行次数最多，shiny app每一次改变都会运行一次。通常应该避免在render函数中放置不需要的代码。这样做会减慢整个应用程序的速度。
#census-app展示
# Load packages ----
library(shiny)
library(maps)
library(mapproj)
# Load data ----
counties <- readRDS("data/counties.rds")
# Source helper functions -----
source("helpers.R")
# User interface ----
ui <- fluidPage(
titlePanel("censusVis"),
sidebarLayout(
sidebarPanel(
helpText("Create demographic maps with
information 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",
label = "Range of interest:",
min = 0, max = 100, value = c(0, 100))
mainPanel(plotOutput("map"))
# Server logic ----
server <- function(input, output) {
output$map <- renderPlot({
data <- switch(input$var,
"Percent White" = counties$white,
"Percent Black" = counties$black,
"Percent Hispanic" = counties$hispanic,
"Percent Asian" = counties$asian)
color <- switch(input$var,
"Percent White" = "darkgreen",
"Percent Black" = "black",
"Percent Hispanic" = "darkorange",
"Percent Asian" = "darkviolet")
legend <- switch(input$var,
"Percent White" = "% White",
"Percent Black" = "% Black",
"Percent Hispanic" = "% Hispanic",
"Percent Asian" = "% Asian")
percent_map(data, color, legend, input$range[1], input$range[2])
# Run app ----
shinyApp(ui, server)
