修改闪亮的ggplot主题答案

【问题标题】：Modify ggplot theme in shiny修改闪亮的ggplot主题
【发布时间】：2019-01-23 21:13:48
【问题描述】：

我有这个用于 K-Means 聚类的应用程序。我希望用户使用selectInput 选择ggplot2 主题。用户将查看下拉菜单并为其情节选择一个主题。

这是我尝试过的：


###################################################################################################################
# Shiny App
###################################################################################################################
ui <- navbarPage("Clustering Demo",
                 tabPanel("K-Means", icon = icon("folder-open"),
                          sidebarLayout(
                            sidebarPanel(
                              sliderInput("num_centers", 
                                          label = h4("Select K (# of Clusters)"),
                                          min = 2,
                                          max = 10,
                                          value = 2),
                              selectInput("theme", label = h4("Select theme for plot"),
                                          choices = list("Light" = theme_light(),
                                                         "Minimal" = theme_minimal()))

                            ),
                            mainPanel(
                              plotOutput("kmeans"))
                          )
                 )
)



server <- function(input, output, session) {

  # K-Means Algorithm
  k_centers <- reactive({kmeans(x = harvard_scaled, centers = input$num_centers)})

  plot_theme <- reactive({input$theme})

  output$kmeans <- renderPlot({

    # Require number of centers
    req(input$num_centers)

    # K Means augmented dataset
    harvard_cluster <- augment(k_centers(), harvard_processed)

    # Static Plot 
    harvard_cluster %>% 
      janitor::clean_names() %>% 
      ggplot(aes(nevents, nplay_video, color = cluster)) +
      geom_point() +
      labs(x = "# of interactions with the course",
           y = "# of play video events",
           color = "Cluster") +
      xlim(0, 52000) +
      ylim(0, 12500) +
      ggtitle(paste("K-Means Clustering of students where", "K =", input$num_centers)) +
      plot_theme()
  })

}




# Create Shiny app object
shinyApp(ui = ui, server = server)

示例数据集：harvard_scaled

harvard_scaled <- structure(c(0.150884824647657, 0.150884824647657, 0.449543446630647, 
0.217253407310543, -0.230734525663942, -0.330287399658272, -0.960788934955696, 
0.715017777282194, 0.449543446630647, -0.147773797335334, -0.380063836655437, 
-0.612353875975541, -0.463024564984046, -0.811459623964201, -1.60788261591884, 
-1.60788261591884, -0.89442035229281, 2.04238943053993, 1.7105465172255, 
2.29127161552575, 0.233845552976265, -0.761683186967036, -0.811459623964201, 
-1.12671039161291, -0.147773797335334, 1.19619000158812, 0.980492107933741, 
1.7105465172255, -0.711906749969871, -0.0648130690067253, -0.844643915295645, 
0.217253407310543, -0.570619818667904, -0.570619818667904, -0.990182090888924, 
0.22009369436402, 1.04308122833602, -0.046166978391628, 1.04308122833602, 
-0.677930938293665, -0.725535119180281, -0.509299178881755, -0.509299178881755, 
0.363713087547369, 0.363713087547369, 0.363713087547369, 1.94675381465822, 
1.84993175183798, 1.68856164713759, -1.226589294275, -1.25079480998006, 
-1.28790993406115, -0.892553177545187, 0.704204008465197, 0.591244935174923, 
0.962396175985825, 1.36582143773681, -1.22416874270449, -0.890939476498183, 
-1.09426580842068, 0.970464681220845, -0.691647397193198, 0.567039419469864, 
-0.885291522833669), .Dim = c(32L, 2L), .Dimnames = list(c("Mazda RX4", 
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout", 
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280", 
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood", 
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic", 
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin", 
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2", 
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora", 
"Volvo 142E"), c("mpg", "disp")), "`scaled:center`" = c(mpg = 20.090625, 
disp = 230.721875), "`scaled:scale`" = c(mpg = 6.0269480520891, 
disp = 123.938693831382))

示例数据集：harvard_processed

harvard_processed <- structure(list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3, 
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 
19.7, 15, 21.4), disp = c(160, 160, 108, 258, 360, 225, 360, 
146.7, 140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 
78.7, 75.7, 71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 
351, 145, 301, 121)), row.names = c("Mazda RX4", "Mazda RX4 Wag", 
"Datsun 710", "Hornet 4 Drive", "Hornet Sportabout", "Valiant", 
"Duster 360", "Merc 240D", "Merc 230", "Merc 280", "Merc 280C", 
"Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood", 
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic", 
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin", 
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2", 
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora", 
"Volvo 142E"), class = "data.frame")

【问题讨论】：

嗨，考虑使用带有 switch.. ``` b
感谢您告诉我@MrFlick。我刚刚添加了harvard_scaled
几乎，现在harvard_processed 不存在了。
@MrFlick 添加了harvard_processed
这些示例数据不起作用，因为现在它们与您在绘图代码中使用的 aes() 不匹配。确保在新的 R 会话中测试您的示例。但在这一点上，它已经不再重要了。如果您将其放入代码中，我的解决方案应该可以工作。但是下次如果有一个合适的reproducible example 会容易得多

标签： r ggplot2 shiny

【解决方案1】：

如果您单击主题选择的下拉菜单，您可能会发现它看起来不像您期望的那样。您不能在 UI 层中存储非原子对象。在代码的其他地方定义主题列表并将它们用作查找会更容易。例如

themes <- list("Light" = theme_light(),
               "Minimal" = theme_minimal())

ui <- navbarPage(..., 
   selectInput("theme", label = h4("Select theme for plot"), choices = names(themes)), 
   ...)

server <- function(input, output, session) {
   ...
   plot_theme <- reactive({themes[[input$theme]]})
   ...
}

【讨论】：