如何在 R 中自定义 plotly boxplots 的悬停文本

Question

我了解如何在 plotly 中自定义散点图的悬停文本，但箱形图不接受 'text' 属性。 Warning message: 'box' objects don't have these attributes: 'text'。我有超过 300 个 x 轴变量，两组（A 或 B）中有编号样本（1-50），我想在同一个箱形图中一起绘制，然后我想区分样本编号和将光标移到异常值上时通过悬停文本进行分组。我想要自定义数据标签而不是自动四分位标签。 plotly 箱线图可能吗？

library(plotly) 
library(magrittr)

plot_ly(melt.s.data, 
          x = ~variable, 
          y = ~value,
          type = 'box', 
          text = ~paste("Sample number: ", Sample_number, 
                       '<br>Group:', Group)) %>% 
        layout(title = "Individual distributions at each x")

这是一些示例数据，仅显示 5 个 x 变量（但当外推到我的 300 时代码应该有效）...

#sample data
set.seed(456)
#Group A
sample.data_a <- data.frame(Class = "red", Group = "A",
                            Sample_number = seq(1,50,by=1), 
                            x1= rnorm(50,mean=0, sd=.5), 
                            x2= rnorm(50,mean=0.5, sd=1.5), 
                            x3= rnorm(50,mean=5, sd=.1), 
                            x4= rnorm(50,mean=0, sd=3.5),
                            x5= rnorm(50,mean=-6, sd=.005))
#Group B
sample.data_b <- data.frame(Class = "red", Group = "B",
                            Sample_number = seq(1,50,by=1), 
                            x1= rnorm(50,mean=0, sd=5.5), 
                            x2= rnorm(50,mean=0.5, sd=7.5), 
                            x3= rnorm(50,mean=5, sd=.01), 
                            x4= rnorm(50,mean=0, sd=.5),
                            x5= rnorm(50,mean=-6, sd=2.05))

#row Bind groups 
sample.data <- rbind(sample.data_a, sample.data_b)

#melting data to have a more graphable format
library(reshape2)
melt.s.data<-melt(sample.data, id.vars=c("Class", "Group","Sample_number"))

以下为类似问题：

Here 好像不行。
这个question类似，只是想添加相关的四分位数信息。
而这个只是 plotly boxplots 中的一个点。

Answer 1

Shiny 可以实现。

library(plotly)
library(shiny)
library(htmlwidgets)

# Prepare data ----
set.seed(456)
#Group A
sample.data_a <- data.frame(Class = "red", Group = "A",
                            Sample_number = seq(1,50,by=1), 
                            x1= rnorm(50,mean=0, sd=.5), 
                            x2= rnorm(50,mean=0.5, sd=1.5), 
                            x3= rnorm(50,mean=5, sd=.1), 
                            x4= rnorm(50,mean=0, sd=3.5),
                            x5= rnorm(50,mean=-6, sd=.005))
#Group B
sample.data_b <- data.frame(Class = "red", Group = "B",
                            Sample_number = seq(1,50,by=1), 
                            x1= rnorm(50,mean=0, sd=5.5), 
                            x2= rnorm(50,mean=0.5, sd=7.5), 
                            x3= rnorm(50,mean=5, sd=.01), 
                            x4= rnorm(50,mean=0, sd=.5),
                            x5= rnorm(50,mean=-6, sd=2.05))
#row Bind groups 
sample.data <- rbind(sample.data_a, sample.data_b)
#melting data to have a more graphable format
melt.s.data <- reshape2::melt(sample.data, 
                              id.vars=c("Class", "Group", "Sample_number"))

# Plotly on hover event ----
addHoverBehavior <- c(
  "function(el, x){",
  "  el.on('plotly_hover', function(data) {",
  "    if(data.points.length==1){",
  "      $('.hovertext').hide();",
  "      Shiny.setInputValue('hovering', true);",
  "      var d = data.points[0];",
  "      Shiny.setInputValue('left_px', d.xaxis.d2p(d.x) + d.xaxis._offset);",
  "      Shiny.setInputValue('top_px', d.yaxis.l2p(d.y) + d.yaxis._offset);",
  "      Shiny.setInputValue('dy', d.y);",
  "      Shiny.setInputValue('dtext', d.text);",
  "    }",
  "  });",
  "  el.on('plotly_unhover', function(data) {",
  "    Shiny.setInputValue('hovering', false);",
  "  });",
  "}")

# Shiny app ----
ui <- fluidPage(
  tags$head(
    # style for the tooltip with an arrow (http://www.cssarrowplease.com/)
    tags$style("
               .arrow_box {
                    position: absolute;
                  pointer-events: none;
                  z-index: 100;
                  white-space: nowrap;
                  background: CornflowerBlue;
                  color: white;
                  font-size: 13px;
                  border: 1px solid;
                  border-color: CornflowerBlue;
                  border-radius: 1px;
               }
               .arrow_box:after, .arrow_box:before {
                  right: 100%;
                  top: 50%;
                  border: solid transparent;
                  content: ' ';
                  height: 0;
                  width: 0;
                  position: absolute;
                  pointer-events: none;
               }
               .arrow_box:after {
                  border-color: rgba(136,183,213,0);
                  border-right-color: CornflowerBlue;
                  border-width: 4px;
                  margin-top: -4px;
               }
               .arrow_box:before {
                  border-color: rgba(194,225,245,0);
                  border-right-color: CornflowerBlue;
                  border-width: 10px;
                  margin-top: -10px;
               }")
  ),
  div(
    style = "position:relative",
    plotlyOutput("myplot"),
    uiOutput("hover_info")
  )
)

server <- function(input, output){
  output$myplot <- renderPlotly({
    plot_ly(melt.s.data, 
            type = "box", 
            x = ~variable, y = ~value, 
            text = paste0("<b> group: </b>", melt.s.data$Group, "<br/>",
                          "<b> sample: </b>", melt.s.data$Sample_number, "<br/>"),
            hoverinfo = "y") %>%
      onRender(addHoverBehavior)
  })
  output$hover_info <- renderUI({
    if(isTRUE(input[["hovering"]])){
      style <- paste0("left: ", input[["left_px"]] + 4 + 5, "px;", # 4 = border-width after
                      "top: ", input[["top_px"]] - 24 - 2 - 1, "px;") # 24 = line-height/2 * number of lines; 2 = padding; 1 = border thickness
      div(
        class = "arrow_box", style = style,
        p(HTML(input$dtext, 
               "<b> value: </b>", formatC(input$dy)), 
          style="margin: 0; padding: 2px; line-height: 16px;")
      )
    }
  })
}

shinyApp(ui = ui, server = server)

Answer 2

一个可能的解决方案可能是使用 ggplot2 包并向您的箱线图添加一个不可见的散点图：

library(ggplot2)
library(plotly)

gg_box <- melt.s.data %>%
  ggplot(aes(x=variable, y=value, text=paste("Group:",Group, "\n",
                                            "Class:", Class))) +
  geom_boxplot()+

  #invisible layer of points
  geom_point(alpha = 0)

gg_box %>%
  ggplotly()

您需要稍微转动一下光标才能看到额外的标签。

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