如何叠加含离散与连续Y轴的散点图和柱状图？

我已创建两个图表：

• 散点图：X轴为时间，Y轴是Tom、Jerry这类离散值
• 柱状图：X轴同样为时间，Y轴是身高这类连续值

尝试将两图叠加到同一画布时，现有实现代码过于繁琐，求更简便的方法。

原图表代码 #

散点图 #

data.scatter <- data.frame(x = c(1, 2, 3, 4, 5), y = c("Tom", "Jerry", "Tom", "Jerry", "Tom"))
ggplot(data.scatter, aes(x = x, y = y)) + geom_point()

柱状图 #

data.bar <- data.frame(x = c(1, 2, 3, 4, 5), y = c(10, 20, 30, 40, 50))
ggplot(data.bar, aes(x = x, y = y)) + geom_bar(stat = "identity")

原尝试代码（繁琐版） #

library(tidyverse)

data.scatter <- data.frame(x = c(1, 2, 3, 4, 5), y = c("Tom", "Jerry", "Tom", "Jerry", "Tom"))
p1 <- ggplot(data.scatter, aes(x = x, y = y)) + geom_point()
p1_data <- ggplot_build(p1)$data[[1]]

data.bar <- data.frame(x = c(1, 2, 3, 4, 5), y = c(10, 20, 30, 40, 50))
p2 <- ggplot(data.bar, aes(x = x, y = y)) + geom_bar(stat = "identity")

p2_data <- ggplot_build(p2)$data[[1]]

p3 <- p2_data %>% ggplot() +
  geom_rect(aes(ymin=ymin,ymax = ymax,xmin = xmin,xmax = xmax)) + 
  geom_text(aes(x=xmin+.45,y=ymax+1,label=ymax)) +
  geom_point(data = p1_data, aes(x = x, y = y*20),inherit.aes = F) + 
  scale_y_continuous(breaks = c(20,40),labels = c("Tom","Jerry")) + 
  labs(x=NULL,y=NULL)

p3

简便解决方案 #

无需提取绘图数据重构，直接在同一ggplot对象中叠加图层，把离散Y值映射为连续数值后自定义刻度标签即可：

代码实现 #

library(ggplot2)

# 准备数据
data.bar <- data.frame(x = c(1, 2, 3, 4, 5), y_height = c(10, 20, 30, 40, 50))
data.scatter <- data.frame(x = c(1, 2, 3, 4, 5), y_name = c("Tom", "Jerry", "Tom", "Jerry", "Tom"))

# 将离散名称映射为连续数值（和你原代码的映射逻辑一致）
data.scatter$y_num <- ifelse(data.scatter$y_name == "Tom", 20, 40)

# 绘制叠加图
ggplot() +
  # 添加柱状图层
  geom_bar(data = data.bar, aes(x = x, y = y_height), stat = "identity", fill = "steelblue") +
  # 添加散点图层
  geom_point(data = data.scatter, aes(x = x, y = y_num), color = "red", size = 3) +
  # 自定义Y轴刻度与标签
  scale_y_continuous(
    breaks = c(10, 20, 30, 40, 50),
    labels = c("10", "Tom", "30", "Jerry", "50")
  ) +
  labs(x = "时间", y = "")

关键逻辑 #

1. 直接在同一画布上调用多个geom_*函数，分别指定对应的数据框，避免复杂的数据提取
2. 把离散的人物名称转换为对应的连续数值，匹配柱状图的Y轴范围
3. 通过scale_y_continuous自定义刻度标签，让Y轴同时展示身高数值和人物名称，实现和你需求一致的效果

内容的提问来源于stack exchange，提问作者tenjyo syu