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ggplot2的geom_errorbar在多个变量之间按降序排列

visualization ggplot2 r

Adrian · 技术社区 · 2 年前

library(ggplot2)
mydat <- data.frame(mean = c(23, 24, 15, 27, 18, 19, 23, 20, 32),
           lower = c(20, 19, 13, 15, 14, 18, 20, 17, 20),
           upper = c(25, 29, 17, 39, 22, 20, 26, 23, 40),
           class = c("A", "B", "C", "A", "B", "C", "A", "B", "C"),
           domain = c("North", "North", "North", "West", "West", "West", "South", "South", "South"))
mydat$class <- as.factor(mydat$class)
mydat$domain <- as.factor(mydat$domain)

mydat %>% ggplot(aes(x = mean, y = class, color = domain, Group = domain, xmin = lower, xmax = upper)) +
  geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + theme_light() + geom_point(position = position_dodge(width = 0.5)) + xlab("Counts")

我想通过减小上限值(即。, upper )误差条的两个 class 以及 domain s.所需输出为:

我尝试了以下代码,但没有达到预期效果:

library(forcats)
mydat %>% ggplot(aes(x = mean, y = class, color = fct_infreq(domain), Group = fct_infreq(domain), xmin = lower, xmax = upper)) +
  geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + theme_light() + geom_point(position = position_dodge(width = 0.5)) + xlab("Counts")

2 回复 | 直到 2 年前

jared_mamrot 2 年前

我不认为有一种“简单”的方法可以实现这一结果;当您根据 max(upper) 所有域的顺序都是“设置”的(尽管我很乐意在这方面被证明是错误的)。

一个潜在的解决方案可能是按类别划分你的绘图,并分别对每个绘图重新排序,例如。

library(tidyverse)

mydat <- data.frame(mean = c(23, 24, 15, 27, 18, 19, 23, 20, 32),
                    lower = c(20, 19, 13, 15, 14, 18, 20, 17, 20),
                    upper = c(25, 29, 17, 39, 22, 20, 26, 23, 40),
                    class = c("A", "B", "C", "A", "B", "C", "A", "B", "C"),
                    domain = c("North", "North", "North", "West", "West", "West", "South", "South", "South"))
mydat$class <- as.factor(mydat$class)
mydat$domain <- as.factor(mydat$domain)

colour_palette <- scales::hue_pal()(3)

mydat %>%
  group_split(class) %>%
  map(~{ggplot(data = .x,
               aes(x = mean, y = fct_reorder(.f = class, .x = upper, .fun = max),
                   color = fct_reorder(.f = domain, .x = upper, .fun = max),
                   Group = fct_reorder(.f = domain, .x = upper, .fun = max),
                   xmin = lower, xmax = upper)) +
  geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + 
  theme_light() + 
  geom_point(position = position_dodge(width = 0.5)) +
      xlab("Counts") +
      ylab("Class") +
      scale_color_manual(values = c("North" = colour_palette[1],
                                    "South" = colour_palette[2],
                                    "West" = colour_palette[3]),
                         name = "Domain")})
#> [[1]]

#> 
#> [[2]]

#> 
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^{创建于2023-10-23

reprex v2.0.2}

如果你“手动”这样做,你可以按照你想要的顺序排列,例如。

library(tidyverse)

mydat <- data.frame(mean = c(23, 24, 15, 27, 18, 19, 23, 20, 32),
                    lower = c(20, 19, 13, 15, 14, 18, 20, 17, 20),
                    upper = c(25, 29, 17, 39, 22, 20, 26, 23, 40),
                    class = c("A", "B", "C", "A", "B", "C", "A", "B", "C"),
                    domain = c("North", "North", "North", "West", "West", "West", "South", "South", "South"))
mydat$class <- as.factor(mydat$class)
mydat$domain <- as.factor(mydat$domain)

colour_palette <- scales::hue_pal()(3)

p1 <- mydat %>%
  filter(class == "A") %>%
  ggplot(aes(x = mean, y = fct_reorder(.f = class, .x = upper, .fun = max),
                   color = fct_reorder(.f = domain, .x = upper, .fun = max),
                   Group = fct_reorder(.f = domain, .x = upper, .fun = max),
                   xmin = lower, xmax = upper)) +
      geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + 
      theme_light(base_size = 18) + 
      geom_point(position = position_dodge(width = 0.5)) +
      xlab("") +
      ylab("") +
      scale_color_manual(values = c("North" = colour_palette[1],
                                    "South" = colour_palette[2],
                                    "West" = colour_palette[3]),
                         name = "Domain") +
  scale_x_continuous(limits = c(10, 45))

p2 <- mydat %>%
  filter(class == "B") %>%
  ggplot(aes(x = mean, y = fct_reorder(.f = class, .x = upper, .fun = max),
             color = fct_reorder(.f = domain, .x = upper, .fun = max),
             Group = fct_reorder(.f = domain, .x = upper, .fun = max),
             xmin = lower, xmax = upper)) +
  geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + 
  theme_light(base_size = 18) + 
  geom_point(position = position_dodge(width = 0.5)) +
  xlab("Counts") +
  ylab("") +
  scale_color_manual(values = c("North" = colour_palette[1],
                                "South" = colour_palette[2],
                                "West" = colour_palette[3]),
                     name = "Domain") +
  theme(legend.position = "none") +
  scale_x_continuous(limits = c(10, 45))

p3 <- mydat %>%
  filter(class == "C") %>%
  ggplot(aes(x = mean, y = fct_reorder(.f = class, .x = upper, .fun = max),
             color = fct_reorder(.f = domain, .x = upper, .fun = max),
             Group = fct_reorder(.f = domain, .x = upper, .fun = max),
             xmin = lower, xmax = upper)) +
  geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) + 
  theme_light(base_size = 18) + 
  geom_point(position = position_dodge(width = 0.5)) +
  xlab("") +
  ylab("") +
  scale_color_manual(values = c("North" = colour_palette[1],
                                "South" = colour_palette[2],
                                "West" = colour_palette[3]),
                     name = "Domain") +
  theme(legend.position = "none") +
  scale_x_continuous(limits = c(10, 45))

library(patchwork)
p3 / p1 / p2

^{创建于2023-10-23

reprex v2.0.2}

ThomasIsCoding 2 年前

我无法计算出与您预期的相同的输出,但希望以下代码对您有同等的意义(其中 domain 信息作为标签添加到每个错误栏)

mydat %>%
    mutate(class = factor(class, names(sort(by(upper, class, max))))) %>%
    arrange(class, desc(upper)) %>%
    mutate(color = factor(n() - row_number()), .by = class) %>%
    ggplot(aes(x = mean, y = class, color = color, Group = domain, xmin = lower, xmax = upper)) +
    geom_errorbar(width = 0.1, position = position_dodge(width = 0.5)) +
    geom_text(aes(label = domain), position = position_dodge(0.5)) +
    theme_light() +
    geom_point(position = position_dodge(width = 0.5)) +
    xlab("Counts")

数据

mydat <- data.frame(
    mean = c(23, 24, 15, 27, 18, 19, 23, 20, 32),
    lower = c(20, 19, 13, 15, 14, 18, 20, 17, 20),
    upper = c(25, 29, 17, 39, 22, 20, 26, 23, 40),
    class = c("A", "B", "C", "A", "B", "C", "A", "B", "C"),
    domain = c("North", "North", "North", "West", "West", "West", "South", "South", "South")
)