r - ggplot2 - 向分组条形图添加差异

Question

我在 ggplot 上绘制以下数据:

library(ggplot2)

DF <- structure(list(Type = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L), .Label = c("Observed", "Simulated"), class = "factor"), 
    variable = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L), .Label = c("EM to V6", 
    "V6 to R0", "R0 to R4", "R4 to R9"), class = "factor"), value = c(28, 
    30, 29, 35, 32, 34, 26, 29)), row.names = c(NA, -8L), .Names = c("Type", 
"variable", "value"), class = "data.frame")

ggplot(DF, aes(variable, value)) +
      geom_bar(aes(fill = Type), position = "dodge", stat="identity", width=.5) +
      geom_text(aes(label=value, group=Type), position=position_dodge(width=0.5), vjust=-0.5) +
      theme_bw(base_size = 18) +
      ylab('Duration (days)') + xlab('Growth stages')

我想知道是否有任何图形方式可以将每组条形图之间的差异添加到图表中？

这是要添加差异的数据框:

DF2 <- data.frame(variable=c("EM to V6", "V6 to R0", "R0 to R4", "R4 to R9"), value=c(2,6,2,3)

最终图表看起来像这样(注意彩色条):

来源:https://www.excelcampus.com/charts/variance-clustered-column-bar-chart/

使用 ggplot 可以吗？

Answer 1

按照rawr的建议，您可以在当前的bars后面添加一层宽度稍小的bars:

library(tidyverse)
diff_df = DF %>%
    group_by(variable) %>%
    spread(Type, value) %>%
    mutate(diff = Simulated - Observed)

ggplot(DF, aes(variable, value)) +
    geom_bar(aes(y = Simulated), data = diff_df, stat = "identity", fill = "grey80", width = 0.4) +
    geom_bar(aes(fill = Type), position = "dodge", stat="identity", width=.5) +
    geom_text(aes(label=value, group=Type), position=position_dodge(width=0.5), vjust=-0.5) +
    geom_text(aes(label = diff, y = Simulated), vjust=-0.5, data = diff_df, hjust = 2, colour = scales::muted("red")) +
    theme_bw(base_size = 18) +
    ylab('Duration (days)') + xlab('Growth stages')

---

更新代码以处理 Observed 有时高于 Simulated:

library(tidyverse)
diff_df = DF %>%
    group_by(variable) %>%
    spread(Type, value) %>%
    mutate(diff = Simulated - Observed,
           max_y = max(Simulated, Observed),
           sim_higher = Simulated > Observed)

ggplot(DF, aes(variable, value)) +
    geom_bar(aes(y = max_y), data = diff_df, stat = "identity", fill = "grey80", width = 0.4) +
    geom_bar(aes(fill = Type), position = "dodge", stat="identity", width=.5) +
    geom_text(aes(label=value, group=Type), position=position_dodge(width=0.5), vjust=-0.5) +
    geom_text(aes(label = diff, y = max_y), vjust=-0.5, data = diff_df %>% filter(sim_higher), 
              hjust = 2, colour = scales::muted("red")) +
    geom_text(aes(label = diff, y = max_y), vjust=-0.5, data = diff_df %>% filter(!sim_higher), 
              hjust = -1, colour = scales::muted("red")) +
    theme_bw(base_size = 18) +
    ylab('Duration (days)') + xlab('Growth stages')