R Shiny应用tabPanel无报错但无法显示plot绘图问题求助

问题根源 #

代码的核心问题出在ui.R中tabPanel的参数使用错误：tabPanel的value参数是可选的、用于给标签页赋值以便程序识别选中状态，不是用来放置标签页内容的，你将plotOutput赋值给了value，导致绘图组件没有被加载到页面中，自然不会显示任何内容。

修复方案 #

1. 修正ui.R代码

删除tabPanel中包裹plotOutput的value =前缀，直接将绘图输出作为标签页的内容参数传入，修正后的完整ui.R代码如下：

library(shiny)

shinyUI(fluidPage(
  
  titlePanel("Data Viz Lab"),
  
  sidebarLayout(
    
    sidebarPanel(
      ## Add X-Variable select element
      selectInput(inputId = "var_x",
                  label = h5("X-Variable"), 
                  choices = c("Structure.Cost", "Land.Value", "Home.Value", "Home.Price.index"), 
                  selected = "Land.Value"),
      
      ## Add Fill Color select element
      selectInput(inputId = "color",
                  label = h5("Fill Color"), 
                  choices = c("brown", "yellow", "green", "blue", "red"), 
                  selected = "brown"),
      
      ## Add log-scale check box
      checkboxInput(inputId = "log",
                    label = "log-sclae for X-variable in Scatterplot?",
                    value = FALSE),
      
      ## Add Y-Variable select element
      selectInput(inputId = "var_y",
                  label = h5("Y-Variable"), 
                  choices = c("Structure.Cost", "Land.Value", "Home.Value", "Home.Price.index"), 
                  selected = "Structure.Cost"),
      
      ## Add Circle-Size side bar
      sliderInput(inputId = "size",
                  label = h5("Circle-Size"),
                  min = 1, 
                  max = 10,
                  value = 3),
      
      ## Add Outlier color select element
      selectInput(inputId = "color_out",
                  label = h5("Outlier Color"), 
                  choices = c("white", "yellow", "green", "blue", "red"), 
                  selected = "white")
      ), 
    
    mainPanel(
      
      tabsetPanel(  # Establish tabset panel
        tabPanel(
          # Tab1
          title = "Histogram",
          plotOutput(outputId = "hist")  # 移除了value=前缀
        ),
        tabPanel(
          # Tab2
          title = "Scatterplot",
          plotOutput(outputId = "scatter")  # 移除了value=前缀
         )
       )
     )
   )
  ))

2. 优化server.R冗余逻辑

避免每次渲染散点图时重复修改全局数据集导致的列名冲突，同时给直方图增加bins参数避免默认警告，修正后的完整server.R代码如下：

library(shiny)
library(ggplot2)
library(sp)
library(dplyr)

# setwd()
landdata = read.csv("landdata.csv")
options(scipen = 999)

shinyServer(function(input, output) {

  ## Plotting Histogram
  output$hist = renderPlot({

    # Plotting
    if (input$log == FALSE){
      ggplot(landdata, aes_string(x = input$var_x)) +
        geom_histogram(color = input$color, bins = 30) # 新增bins参数避免警告
    }else{
      ggplot(landdata, aes_string(x = input$var_x)) +
        geom_histogram(color = input$color, bins = 30) +
        scale_x_log10(input$var_x)
    }

  })
  
  ## Plotting Scatter plot
  output$scatter = renderPlot({
    
    # Data pre-processing
    p = ggplot(data = landdata, aes_string(x = input$var_x, y = input$var_y)) +
      geom_point() +
      stat_ellipse(type = "norm", level = 0.95, color = "black")
    
    build = ggplot_build(p)$data
    pts = build[[1]]
    elli = build[[2]]
    Outlier = point.in.polygon(pts$x, pts$y, elli$x, elli$y)
    
    # 改用临时变量存储，不修改全局landdata避免列重复
    tmp_landdata = cbind(landdata, Outlier)
    tmp_landdata$Outlier = ifelse(tmp_landdata$Outlier == 0, yes = "Y", no = "N") %>% factor(level = c("Y", "N"))
    
    # Plotting
    if (input$log == FALSE){
      ggplot(tmp_landdata, aes_string(x = input$var_x, y = input$var_y)) +
        geom_point(aes(color = Outlier), size = input$size) +
        scale_color_manual(values = c(input$color, input$color_out))
    }else{
      ggplot(tmp_landdata, aes_string(x = input$var_x, y = input$var_y)) +
        geom_point(aes(color = Outlier), size = input$size) +
        scale_color_manual(values = c(input$color, input$color_out)) +
        scale_x_log10(input$var_x)
    }
      
  })
  
})

修改后重新运行应用即可正常展示两个标签页的绘图内容。

内容的提问来源于stack exchange，提问作者HsunHung Chu