使用tidyverse包和facet_grid可以更干净地解决这个问题：

library(tidyverse)
read_tsv("tmp.tsv", col_types = "ccci") %>%  
ggplot(aes(x=month, y=count, fill=type)) + geom_col() + facet_grid(.~id)

请注意，您必须在col_types参数中将前三列指定为“character”，否则看起来不太好。用有意义的东西替换数字代码会更好（例如，将月份变成有序因子“January”，“February”而不是1，2;类型和ID类似）。

假设您想要将id绘制为x轴，并排显示月份，并堆叠不同类型，您可以按月份拆分 Dataframe ，并为每个月份添加一个条形图层，为第二个月的条形图移动x一个量，以便将它们分隔开：

barwidth = 0.35

month_one <- filter(df, month == 1) %>% 
    group_by(id) %>% arrange(-type) %>% 
    mutate(pos = cumsum(count) - count / 2)   # calculate the position of the label

month_two <- filter(df, month == 2) %>% 
    group_by(id) %>% arrange(-type) %>% 
    mutate(pos = cumsum(count) - count / 2)

ggplot() + 
    geom_bar(data = month_one, 
             mapping = aes(x = id, y = count, fill = as.factor(type)), 
             stat="identity", 
             position='stack', 
             width = barwidth) + 
    geom_text(data = month_one, 
              aes(x = id, y = pos, label = count )) + 
    geom_bar(data = filter(df, month==2), 
             mapping = aes(x = id + barwidth + 0.01, y = count, fill = as.factor(type)), 
             stat="identity", 
             position='stack' , 
             width = barwidth) + 
    geom_text(data = month_two, 
              aes(x = id + barwidth + 0.01, y = pos, label = count )) + 
    labs(fill  = "type")

给出：

dput(df)
structure(list(id = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), month = c(1L, 1L, 1L, 2L, 2L, 
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L), type = c(1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L), count = c(10L, 9L, 26L, 60L, 90L, 80L, 10L, 9L, 26L, 60L, 
90L, 80L, 10L, 9L, 26L, 60L, 90L, 80L)), .Names = c("id", "month", 
"type", "count"), class = "data.frame", row.names = c(NA, -18L
))