ggplot2：圆形条形图操作以实现可扩展性

Question

序言： 我最近有这个线程

目标

复制这个情节

当前代码

library(tidyverse)

data <- data.frame(
  labels = c("A","B","C","D","E","F","G","H"),
  values = c(88, 61, 56, 77, 83, 63, 42, 60)
) %>%
  mutate(
    bar_color = case_when(
      values < 62 ~ "#f2452e",
      values < 85 ~ "#76c5d0",
      values >= 85 ~ "#4b7d84",
    )
  )

ggplot(data, aes(x = labels, y = values)) +
  geom_bar(aes(fill = bar_color),
           stat = "identity", size = 1,
           color = "gray20", width = 1,
           alpha = 0.8) +
  coord_polar(start = -(pi / 8)) +
  scale_fill_identity() +
  theme(
    panel.grid.major.y = element_line(
      linewidth = .8,
      color = c("transparent", alpha("grey80", 0.5))
    ),
    axis.title = element_blank(),
    panel.background = element_blank(),
    axis.ticks.y = element_blank(),
    axis.text = element_blank(),
  ) +
  geom_hline(yintercept = 96.5,
             color = "grey90", size = 3) +
  scale_y_continuous(breaks = seq(0, 95, 5)) +
  geom_segment(aes(x = 1.5:8.5, y = 0, yend = 95),
               inherit.aes = FALSE, color = alpha("grey20", 0.5)) +
  geom_hline(yintercept = 94,
             color = "grey20", size = 1) +
  geom_label(aes(label = labels, y = 96), fill = "white", size = 6)

当前剧情：

问题

价值：

1. breaks

   在

   scale_y_continuous()

2. yintercept

   在

   geom_hline()

3. yend

   中

   geom_segment()

   ；和

4. y

   在

   geom_label()

全部都是硬编码的。当

data$values

变化时，尤其是在95以上（最大为100）时，这成为挑战。我需要帮助以确保问题

#1

到

#4

的值保持在

100

左右以覆盖

data$values

的所有可能值

Answer 1

将我的评论作为答案更加明确。

• 从

  data$values

中提取最大值
• 在绘图部分使用它来调整列表的不同层

我也：

• 在

  size

  中将

  linewidth

  替换为

  geom_hline

  ，因为它会引发弃用警告
• 在一些 ')' 之前删除了一些额外的 ','

结果如下：

library(tidyverse)

data <- data.frame(
  labels = c("A","B","C","D","E","F","G","H"),
  values = c(88, 61, 56, 77, 83, 63, 42, 98)
) %>%
  mutate(
    bar_color = case_when(
      values < 62 ~ "#f2452e",
      values < 85 ~ "#76c5d0",
      values >= 85 ~ "#4b7d84"))

ymax <- max(data$values)

p <- ggplot(data, aes(x = labels, y = values)) +

     geom_bar(aes(fill = bar_color),
           stat = "identity", size = 1,
           color = "gray20", width = 1,
           alpha = 0.8) +

     coord_polar(start = -(pi / 8)) +   scale_fill_identity() +

     theme(
    panel.grid.major.y = element_line(
      linewidth = .8,
      color = c("transparent", alpha("grey80", 0.5))),
    axis.title = element_blank(),
    panel.background = element_blank(),
    axis.ticks.y = element_blank(),
    axis.text = element_blank()) +

     geom_hline(yintercept = ymax + 8.5,
             color = "grey90", linewidth = 3) +

     scale_y_continuous(breaks = seq(0, ymax + 7, 5)) +

     geom_segment(aes(x = 1.5:8.5, y = 0, yend = ymax + 7),
               inherit.aes = FALSE, color = alpha("grey20", 0.5)) +

     geom_hline(yintercept = ymax + 6,
             color = "grey20", linewidth = 1) +

     geom_label(aes(label = labels, y = ymax + 8), fill = "white", size = 6)

print(p)

结果：