【问题标题】：How to link plotly traces for legend and colour selection?如何链接情节痕迹以进行图例和颜色选择？
【发布时间】：2016-07-24 18:31:25
【问题描述】：

问题

我在shiny 应用程序中将一些ggplot/ggvis 图迁移到plotly。我遇到了一个关于跟踪链接的问题。我希望能够在图例上显示/隐藏 group 的痕迹，这在相关数据帧之间共享。

最小的工作示例

# load libraries
library(dplyr)
library(plotly)
library(viridis)

# contrived data to represent actual data points
df1 <- data.frame(x = rnorm(100),
                  y = rnorm(100),
                  group = rep(c("G1", "G2", "G3", "G4"), 25))

# contrived data to represent theoretical relationship
df2 <- data.frame(x = c(rep(-2, 4), rep(2, 4)),
                  y = c(seq(1.9, 1, -0.3), seq(-1, -1.9, -0.3)),
                  group = rep(c("G1", "G2", "G3", "G4"), 2))

# create plot with scatter and line traces
df1 %>%
  plot_ly(x = x,
          y = y,
          color = group,
          colors = viridis(n_distinct(group)),
          mode = "markers") %>%
  add_trace(x = x,
            y = y,
            color = group,
            colors = viridis(n_distinct(group)),
            mode = "lines",
            data = df2)

目前的尝试

我的在线搜索，尤其是阅读plotly 文档并没有让我走得太远。

我可以将showlegend = FALSE 添加到第二个跟踪。这确实是解决挑战的一部分，但是，我仍然想根据 group 值显示/隐藏该跟踪。

可能的解决方案

基于plotly 的体系结构，似乎如果我可以将散点图和线放在每个group 的一条迹线上，那么我将获得所需的行为。但是，似乎一个跟踪可能只有一个“模式”，这就是我采用我所拥有的方法的原因。

如果我继续我已经开始的路径，我想我需要以某种方式捕获图例的“点击”事件并显示/隐藏 group 痕迹......但我不确定在哪里开始吧。

为后人重温历史

自首次提出此问题以来，ggplot2 和 plotly 在此期间发生了几处更改。在当前版本 (4.7.1) 中，有一个参数 legendgroup 用于解决问题。

懒惰的代码

请原谅在优雅编码上付出的最小努力，但是，MWE 的这个扩展展示了按组显示/隐藏跟踪的能力。

df1_G1 <- df1 %>% filter(group == "G1")
df2_G1 <- df2 %>% filter(group == "G1")
df1_G2 <- df1 %>% filter(group == "G2")
df2_G2 <- df2 %>% filter(group == "G2")
df1_G3 <- df1 %>% filter(group == "G3")
df2_G3 <- df2 %>% filter(group == "G3")
df1_G4 <- df1 %>% filter(group == "G4")
df2_G4 <- df2 %>% filter(group == "G4")

plot_ly(type = "scatter", mode = "markers") %>%
  add_trace(df1_G1, x = df1_G1$x, y = df1_G1$y, color = I("red"),
            legendgroup = "G1", name = "G1 - scatter") %>%
  add_trace(df2_G1, x = df2_G1$x, y = df2_G1$y, color = I("red"),
            legendgroup = "G1", name = "G1 - line", mode = "lines") %>%
  add_trace(df1_G2, x = df1_G2$x, y = df1_G2$y, color = I("green"), 
            legendgroup = "G2", name = "G2 - scatter") %>%
  add_trace(df2_G2, x = df2_G2$x, y = df2_G2$y, color = I("green"),
            legendgroup = "G2", name = "G2 - line", mode = "lines") %>%
  add_trace(df1_G3, x = df1_G3$x, y = df1_G3$y, color = I("blue"),
            legendgroup = "G3", name = "G3 - scatter") %>%
  add_trace(df2_G3, x = df2_G3$x, y = df2_G3$y, color = I("blue"),
            legendgroup = "G3", name = "G3 - line", mode = "lines") %>%
  add_trace(df1_G4, x = df1_G4$x, y = df1_G4$y, color = I("orange"), 
            legendgroup = "G4", name = "G4 - scatter") %>%
  add_trace(df2_G4, x = df2_G4$x, y = df2_G4$y, color = I("orange"), 
            legendgroup = "G4", name = "G4 - line", mode = "lines")

样本输出

显示取消选择的第一组G1。另请注意，已使颜色在同一组的散点和线迹之间匹配。

【讨论】：