如何在 R 中为 plotly boxplots 自定义悬停文本 [英] How to customize hover text for plotly boxplots in R
本文介绍了如何在 R 中为 plotly boxplots 自定义悬停文本的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我了解如何在 plotly 中自定义散点图的悬停文本，但箱形图不接受文本"属性.警告消息:box"对象没有这些属性:text".我有超过 300 个 x 轴变量，并且在两组(A 或 B)中有编号的样本(1-50)，我想在同一个箱形图中一起绘制，然后我想区分样本数和将光标移动到异常值上时通过悬停文本进行分组.我想要我的自定义数据标签而不是自动四分位数标签.plotly 箱线图有可能吗?
图书馆(情节)图书馆(magrittr)plot_ly(melt.s.data,x = ~变量，y = ~值，类型 = '盒子',text = ~paste("样品编号:", Sample_number,'<br>组:', 组)) %>%layout(title = "每个 x 的个体分布")这是一些仅显示 5 x 变量的示例数据(但当外推到我的 300 时，代码应该可以工作)...
#样本数据设置种子(456)#A组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))#B组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 绑定组sample.data <- rbind(sample.data_a, sample.data_b)#melting 数据以具有更可图形化的格式图书馆(重塑2)melt.s.data<-melt(sample.data, id.vars=c("Class", "Group","Sample_number"))以下是类似的问题:
I understand how to customize the hover text for scatter plots in
plotly, but box plots do not accept the 'text' attribute.Warning message: 'box' objects don't have these attributes: 'text'. I have over 300 x-axis variables and there are numbered samples(1-50) in two groups(A or B) that I want to plot together in the same box plot, then I'd like to differentiate between the sample numbers and groups through hover text when moving the cursor over outliers. I'd like to have my custom data labels instead of the automatic quartile labels. Is that possible withplotlyboxplots?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")Here is some sample data showing only 5 x variables (but the code should work when extrapolated to my 300)...
#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"))The following are similar questions:
- Here it seems like it is not possible.
- This question is similar, but only wants to add relevant quartile info.
- And this question is only about a single point in plotly boxplots.
解决方案It's possible with Shiny.
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)这篇关于如何在 R 中为 plotly boxplots 自定义悬停文本的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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