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R shiny教程-5:调用R程序和导入数据

R shiny教程-5:调用R程序和导入数据

作者: JeremyL | 来源:发表于2020-10-03 18:26 被阅读0次
    Census app views

    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

      App folder with data subfolder

    数据导入:

    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 mapsmapprojR 包。

    install.packages(c("maps", "mapproj"))
    

    helpers.R中有一个percent_map函数,参数如下:

    Argument Input
    var a column vector from the counties.rds dataset
    color any character string you see in the output of colors()
    legend.title A character string to use as the title of the plot’s legend
    max A parameter for controlling shade range (defaults to 100)
    min A parameter for controlling shade range (defaults to 0)
    library(maps)
    library(mapproj)
    source("census-app/helpers.R")
    counties <- readRDS("census-app/data/counties.rds")
    percent_map(counties$white, "darkgreen", "% White")
    
    Percent white map

    #加载文件和文件路径

    • 在上面的代码中,首先导入了需要的r包:
    library(maps)
    library(mapproj)
    

    调用helpers.R

    source("census-app/helpers.R")
    
    • 导入数据:
    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

    #执行

    第一次调用runApp时,Shiny会运行整个脚本。


    Run once

    每当新的用户访问应用程序,Shiny 就会运行server一次,为每个用户构建一组不同的响应对象。

    Run once per user

    当用户使用工具交互并更改值时,Shiny将会重新运行分配给每个反应对象的R表达式,这些反应对象依赖于值被改变的工具。如果用户非常活跃,这些表达式可能会在一秒钟内多次重新运行。

    Run many times

    程序运行的额规律:

    • 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)
    
    Census app

    #总结:

    • 放置app.R的位置将会是Shiny app的工作目录
    • server前的代码只会在Shiny 中运行一次
    • server中的代码会多次运行,代码太多会使程序运行速度减慢

    系列文章:
    R shiny教程-1:一个 Shiny app的基本组成部分
    R shiny教程-2:布局用户界面
    R shiny教程-3:添加小部件到Shiny App
    R shiny教程-4:Shiny app响应式结果展示
    Shiny Server安装

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