您可以尝试：

library(tidyverse)
# some data
data <- mtcars %>%  
  mutate(car = rownames(mtcars)) %>% 
  slice(1:6) %>% 
  select(car, disp, hp) 

data %>% 
  gather(key, value, -car) %>% 
  group_by(car) %>% 
  mutate(qsec_value = median(value)) %>% 
  mutate(qsec = factor("qsec")) %>% 
  ggplot() +
    geom_col(aes(x=car, y=value, fill = key), position = "dodge") +
    geom_point(aes(x=car, y=qsec_value,color = qsec)) +
    geom_line(aes(x=car, y=qsec_value, color = qsec, group =1)) +
    scale_colour_manual(name= "", values = 1) +
     theme(legend.position = "top", 
           legend.title = element_blank())

代码更少，结果相同：

data %>% 
  pivot_longer(-1) %>% 
  ggplot(aes(x = car)) + 
    geom_col(aes(y=value, fill = name), position = "dodge") + 
    stat_summary(aes(y=value, group=1, color="qseq"), fun = "median", geom = "point")+
    stat_summary(aes(y=value, group=1, color="qseq"), fun = "median", geom = "line")+
    scale_colour_manual(name= "", values = 1)

你需要另一个图层，因为geom_line是连续数据，你需要把你的x值当作线图层。这样做，数据的顺序就变得至关重要了，因此你也必须对它排序：

gather(df, key = var, value = value, disp, hp, qsec) %>% 
  arrange(car) %>% 
  {
    print(
      ggplot() +
        geom_bar(stat = 'identity', position = 'dodge', data = filter(., var != "qsec"), mapping = aes(x = car, y = value, fill = var)) +
        geom_line(mapping = aes(x = 1:length(car), y = value), data = filter(., var == "qsec"))
    )
  }

• • 编辑：**

顺便说一句，您可以通过调用plotly::ggplotly()来检查qsec到相应x值的正确顺序，然后您可以更好地读取这些值并将它们与df进行比较，因为如果您指向元素，它们就会显示出来...