如何在绘图中使用多个组，但仅使用定义数量的图例组

假设我有多个不同细胞的时间序列，我可以根据它们是否接受治疗来分割它们 - 我如何绘制所有单独的时间序列（不平均），但根据绘图中的治疗对它们进行分组？

它与 ggplot 完美配合 - 我知道我可以从那里使用 ggplotly - 但有完整的情节方式吗？

以下是一些虚拟数据：

library("dplyr")
library("plotly")

cell <- c(rep("a", 10), rep("b", 10),  rep("c", 10),  rep("d", 10),  rep("e", 10), rep("f", 10))
group <- c(rep("Untreated", 10), rep("Treated", 30), rep("Unknown", 20))
time <- rep(1:10, times=6)
value <- c(runif(60))

df <- data.frame(cell, group, time, value)



# I want this in plotly:
ggplot(df, aes(x=time, y=value, group=cell, color=group)) +
  geom_line()


# For many "cells" this will explode the legend (my real data have hundreds of cells)
plot_ly(df, x=~time, y=~value, split=~cell, color=~group,
        type="scatter", mode="line")


# This works but it connects the last and the first timepoint
plot_ly(df, x=~time, y=~value, group=~cell, color=~group,
        type="scatter", mode="line")

I need this:

But plotly gives me this (too many legendgroups for many cells):

Or this (it connects start and end of individual cells):

有没有什么办法可以用plotly 来做到这一点——或者我需要使用ggplotly 吗？

Edit:

• 新的和扩展的虚拟数据
• 新地块

您可以使用legendgroup并通过隐藏重复的跟踪名称showlegend.

另请参阅：https://plotly.com/r/legend/#grouped-legend https://plotly.com/r/legend/#grouped-legend

Edit:@JulianStopp修改示例数据后： 这是寻找隐藏在图例中的痕迹的通用方法。抱歉切换到data.table但我不熟悉dplyr:

library(data.table)
library(plotly)

cell <- c(rep("a", 10), rep("b", 10),  rep("c", 10),  rep("d", 10),  rep("e", 10), rep("f", 10))
group <- c(rep("Untreated", 10), rep("Treated", 30), rep("Unknown", 20))
time <- rep(1:10, times=6)
value <- c(runif(60))

DF <- data.frame(cell, group, time, value)

setDT(DF)
setorder(DF, group, cell, time)
showlegendDF <- DF[, .SD[1], by = .(group, time), .SDcols = c("cell")][, showlegend := TRUE] # find first trace for each group

DF <- showlegendDF[DF, on = c("group", "cell", "time")] # join
DF[, i := .GRP, by = .(group, cell)] # create trace indices
# set(DF, which(is.na(DF[["showlegend"]])), "showlegend", FALSE) # replace NAs with FALSE

plot_ly(DF, x=~time, y=~value, split=~cell, legendgroup = ~group, name = ~group, color = ~group,
        type="scatter", mode="line") %>% style(showlegend = FALSE, traces = unique(DF[is.na(showlegend), i]))

初步回答：

library("dplyr")
library("plotly")

cell <- c(rep("a", 10), rep("b", 10),  rep("c", 10))
group <- c(rep("Untreated", 10), rep("Treated", 20))
time <- c(seq(1:10), seq(1:10), seq(1:10))
value <- c(runif(30))

df <- data.frame(cell, group, time, value)

plot_ly(df, x=~time, y=~value, split=~cell, legendgroup = ~group, name = ~group, color = ~group,
        type="scatter", mode="line") %>% style(showlegend = FALSE, traces = 2)