在情节子图中合并图例

Question

我有几个组，每个组都有几个 classes 我测量了连续值：

set.seed(1)

df <- data.frame(value = c(rnorm(100,1,1), rnorm(100,2,1), rnorm(100,3,1),
                           rnorm(100,3,1), rnorm(100,1,1), rnorm(100,2,1),
                           rnorm(100,2,1), rnorm(100,3,1), rnorm(100,1,1)),
                 class = c(rep("c1",100), rep("c2",100), rep("c3",100),
                           rep("c2",100), rep("c4",100), rep("c1",100),
                           rep("c4",100), rep("c3",100), rep("c2",100)),
                 group = c(rep("g1",300), rep("g2",300), rep("g3",300)))

df$class <- factor(df$class, levels =c("c1","c2","c3","c4"))
df$group <- factor(df$group, levels =c("g1","g2","g3"))

并非数据中的每个组都具有相同的 classes，或者换句话说，每个组都有所有 classes 的子集。

我正在尝试为每个组生成 R plotly 密度曲线，color-coded 通过 class，然后使用 color-coded 将它们全部组合成一个图 plotly的subplot函数。

这就是我正在做的事情：

library(dplyr)
library(ggplot2)
library(plotly)


set.seed(1)

df <- data.frame(value = c(rnorm(100,1,1), rnorm(100,2,1), rnorm(100,3,1),
                           rnorm(100,3,1), rnorm(100,1,1), rnorm(100,2,1),
                           rnorm(100,2,1), rnorm(100,3,1), rnorm(100,1,1)),
                 class = c(rep("c1",100), rep("c2",100), rep("c3",100),
                           rep("c2",100), rep("c4",100), rep("c1",100),
                           rep("c4",100), rep("c3",100), rep("c2",100)),
                 group = c(rep("g1",300), rep("g2",300), rep("g3",300)))

df$class <- factor(df$class, levels =c("c1","c2","c3","c4"))
df$group <- factor(df$group, levels =c("g1","g2","g3"))

plot.list <- lapply(c("g1","g2","g3"), function(g){
  density.df <- do.call(rbind,lapply(unique(dplyr::filter(df, group == g)$class),function(l)
    ggplot_build(ggplot(dplyr::filter(df, group == g & class == l),aes(x=value))+geom_density(adjust=1,colour="#A9A9A9"))$data[[1]] %>%
      dplyr::select(x,y) %>% dplyr::mutate(class = l)))
  plot_ly(x = density.df$x, y = density.df$y, type = 'scatter', mode = 'lines',color = density.df$class) %>%
    layout(title=g,xaxis = list(zeroline = F), yaxis = list(zeroline = F))
})
subplot(plot.list,nrows=length(plot.list),shareX=T)

给出：

我想解决的问题是：

让图例只出现一次（现在它对每个组重复）合并所有 classes
让标题出现在每个子图中，而不是只出现在最后一个图中。（我知道我可以简单地将群组名称作为 x-axis 标题，但我宁愿保存 space 因为实际上我有 3 个以上的群组）

Answer 1

您可以使用以下代码

library(tidyverse)
library(plotly)

ggplotly(
  ggplot(df, aes(x=value, col = class)) + 
  geom_density(adjust=1) + 
  facet_wrap(~group, ncol = 1) +
    theme_minimal() + 
    theme(legend.position = 'top')
)

这给了我下面的情节

Answer 2

使用 plot_ly() 有点棘手，至少如果您想坚持使用 color 参数从数据生成多个轨迹。

您需要定义一个 legendgroup 并考虑您的 class 变量。然而，此 legendgroup 不会将图例项目合并为一个（它只是将它们分组）。

相应地，为了避免图例中的重复条目，您需要为要隐藏的痕迹（关于图例）设置 showlegend = FALSE。

编辑： 这可以通过 plotly::style:

完成

set.seed(1)

df <- data.frame(value = c(rnorm(100,1,1), rnorm(100,2,1), rnorm(100,3,1),
                           rnorm(100,3,1), rnorm(100,1,1), rnorm(100,2,1),
                           rnorm(100,2,1), rnorm(100,3,1), rnorm(100,1,1)),
                 class = c(rep("c1",100), rep("c2",100), rep("c3",100),
                           rep("c2",100), rep("c4",100), rep("c1",100),
                           rep("c4",100), rep("c3",100), rep("c2",100)),
                 group = c(rep("g1",300), rep("g2",300), rep("g3",300)))

df$class <- factor(df$class, levels =c("c1","c2","c3","c4"))
df$group <- factor(df$group, levels =c("g1","g2","g3"))

library(dplyr)
library(ggplot2)
library(plotly)

plot.list <- lapply(c("g1","g2","g3"), function(g){
  density.df <- do.call(rbind,lapply(unique(dplyr::filter(df, group == g)$class),function(l)
    ggplot_build(ggplot(dplyr::filter(df, group == g & class == l),aes(x=value))+geom_density(adjust=1,colour="#A9A9A9"))$data[[1]] %>%
      dplyr::select(x,y) %>% dplyr::mutate(class = l)))

  p <- plot_ly(data = density.df, x = ~x, y = ~y, type = 'scatter', mode = 'lines', color = ~class, legendgroup = ~class, showlegend = FALSE) %>%
    layout(xaxis = list(zeroline = F), yaxis = list(zeroline = FALSE)) %>%
    add_annotations(
      text = g,
      x = 0.5,
      y = 1.1,
      yref = "paper",
      xref = "paper",
      xanchor = "middle",
      yanchor = "top",
      showarrow = FALSE,
      font = list(size = 15)
    )
  if(g == "g1"){
    p <- style(p, showlegend = TRUE)
  } else if(g == "g2"){
    p <- style(p, showlegend = TRUE, traces = 3)
  } else {
    p <- style(p, showlegend = FALSE)
  }
  p
})

subplot(plot.list, nrows = length(plot.list), shareX = TRUE) # margin = 0.01

初步回答： 这可以通过仅为第一个图设置 showlegend = TRUE 并通过虚拟数据强制它显示所有可用的 classes 来完成。请看以下内容：

set.seed(1)

df <- data.frame(value = c(rnorm(100,1,1), rnorm(100,2,1), rnorm(100,3,1),
                           rnorm(100,3,1), rnorm(100,1,1), rnorm(100,2,1),
                           rnorm(100,2,1), rnorm(100,3,1), rnorm(100,1,1)),
                 class = c(rep("c1",100), rep("c2",100), rep("c3",100),
                           rep("c2",100), rep("c4",100), rep("c1",100),
                           rep("c4",100), rep("c3",100), rep("c2",100)),
                 group = c(rep("g1",300), rep("g2",300), rep("g3",300)))

df$class <- factor(df$class, levels =c("c1","c2","c3","c4"))
df$group <- factor(df$group, levels =c("g1","g2","g3"))

library(dplyr)
library(ggplot2)
library(plotly)

plot.list <- lapply(c("g1","g2","g3"), function(g){
  density.df <- do.call(rbind,lapply(unique(dplyr::filter(df, group == g)$class),function(l)
    ggplot_build(ggplot(dplyr::filter(df, group == g & class == l),aes(x=value))+geom_density(adjust=1,colour="#A9A9A9"))$data[[1]] %>%
      dplyr::select(x,y) %>% dplyr::mutate(class = l)))
  
  p <- plot_ly(data = density.df, x = ~x, y = ~y, type = 'scatter', mode = 'lines', color = ~class, legendgroup = ~class, showlegend = FALSE) %>%
    layout(xaxis = list(zeroline = F), yaxis = list(zeroline = FALSE)) %>%
    add_annotations(
      text = g,
      x = 0.5,
      y = 1.1,
      yref = "paper",
      xref = "paper",
      xanchor = "middle",
      yanchor = "top",
      showarrow = FALSE,
      font = list(size = 15)
    )
  if(g == "g1"){
    dummy_df <- data.frame(class = unique(df$class))
    dummy_df$x <- density.df$x[1]
    dummy_df$y <- density.df$y[1]
    p <- add_trace(p, data = dummy_df, x = ~x, y = ~y, color = ~class, type = "scatter", mode = "lines", showlegend = TRUE, legendgroup = ~class, hoverinfo = 'none')
  }
  p
})

subplot(plot.list, nrows = length(plot.list), shareX = TRUE)

另一种方法（避免虚拟数据解决方法）是在循环中创建每个跟踪（或通过 lapply）并根据项目的第一次出现来控制它 legend-visibilty。

此外，我认为应该可以使用 ?plotly::style 控制图例项的可见性。但是，我目前无法控制单个痕迹。我提出了一个问题 here。

关于次要情节的标题，请参阅 this。

在情节子图中合并图例

Merging legends in plotly subplot

r

legend

subplot

plotly

r-plotly