基于唯一列填充颜色向量答案

【问题标题】：Fill colour vector based on unique columns基于唯一列填充颜色向量
【发布时间】：2020-10-01 12:32:26
【问题描述】：

我正在使用 c3 绘制一些线条。如果两行完全相同，C3 将覆盖它们并在图例中使用不同颜色。我希望图例中的颜色相同。

这里有一些例子

# If two lines are identical, colour them the same

library(tidyverse)
library(c3)

# Dark red, blue, orange, black, purple
cbpal <- c("#800000", "#4363d8", "#f58231", "#000000", "#dcbeff")

# Companies A and B are should be dark red. Companies C and D should be blue
df1 <- tibble(
  date = seq(as.Date("2020-01-01"), by = "month", length.out = 4),
  comp_A = rep(4, 4),
  comp_B = rep(4, 4),
  comp_C = rep(2, 4),
  comp_D = rep(2, 4)
)

# Company A and B should be dark red. Companies C, D, E, should all be blue
df2 <- tibble(
  date = seq(as.Date("2020-01-01"), by = "month", length.out = 4),
  comp_A = rep(4, 4),
  comp_B = rep(4, 4),
  comp_C = rep(3, 4),
  comp_D = rep(3, 4),
  comp_E = rep(3, 4)
)

# Company A and B should be dark red. Companies C, D, should all be blue
# Companies E, F, should all be orange
df3 <- tibble(
  date = seq(as.Date("2020-01-01"), by = "month", length.out = 4),
  comp_A = rep(4, 4),
  comp_B = rep(4, 4),
  comp_C = rep(3, 4),
  comp_D = rep(3, 4),
  comp_E = rep(2, 4),
  comp_F = rep(2, 4)
)

c3(df1)
df1_pal <- c("#800000", "#800000", "#4363d8","#4363d8")
c3(df1) %>% 
  c3_color(df1_pal)

c3(df2)
df2_pal <- c("#800000", "#800000", "#4363d8","#4363d8", "#4363d8")
c3(df2) %>% 
  c3_color(df2_pal)

c3(df3)
df3_pal <- c("#800000", "#800000", "#4363d8","#4363d8", "#f58231", "#f58231")
c3(df3) %>% 
  c3_color(df3_pal)

在第一个数据帧中，有4行，但是comp_A和comp_B是一样的，comp_C和comp_D是一样的。为了创建颜色矢量，我从色盲调色板中获取第一种颜色#800000，并使用它进行颜色 comp_A。我注意到 comp_B 是相同的，并使其颜色相同，#800000。 comp_C 不同，所以我再次进入cbpal 并获取第二种颜色。最终，我得到了调色板，df1_pal <- c("#800000", "#800000", "#4363d8","#4363d8")，如图所示。

还有两个例子。在所有情况下，数据框将按 y 轴值的降序排列。

如何以编程方式创建这些颜色矢量？

【问题讨论】：

标签： r

【解决方案1】：

每列的哈希值可用于将列映射到颜色。

get_cols 获取每列的哈希值。哈希映射到一个索引，该索引与cbpal 一起使用以获取颜色。

get_cols <- function(df) {
  hashes <-
    df %>%
    select(-date) %>%
    map_chr(digest::digest)
  
  cbpal[match(hashes, unique(hashes))]
}

get_cols(df1)
#> [1] "#800000" "#800000" "#4363d8" "#4363d8"

get_cols(df2)
#> [1] "#800000" "#800000" "#4363d8" "#4363d8" "#4363d8"

get_cols(df3)
#> [1] "#800000" "#800000" "#4363d8" "#4363d8" "#f58231" "#f58231"

【讨论】：