ggplot中不同宽度的堆积条形图

Question

我尝试构建一个不同宽度的堆积条形图，宽度表示分配的平均数量，而高度表示分配的数量。

接下来，你会发现我的可重现数据：

procedure = c("method1","method2", "method3", "method4","method1","method2", "method3", "method4","method1","method2", "method3","method4")
sector =c("construction","construction","construction","construction","delivery","delivery","delivery","delivery","service","service","service","service") 
number = c(100,20,10,80,75,80,50,20,20,25,10,4)
amount_mean = c(1,1.2,0.2,0.5,1.3,0.8,1.5,1,0.8,0.6,0.2,0.9) 

data0 = data.frame(procedure, sector, number, amount_mean)

当使用 geom_bar 并在 aes 中包含宽度时，我收到以下错误消息：

position_stack requires non-overlapping x intervals. Furthermore, the bars are no longer stacked. 

bar<-ggplot(data=data0,aes(x=sector,y=number,fill=procedure, width = amount_mean)) + 
geom_bar(stat="identity") 

我还查看了 mekko-package，但似乎这仅适用于条形图。

这里是我最后想要的（不是基于上面的数据）：

知道如何解决我的问题吗？

Answer 1

我也尝试过同样的方法，geom_col()，但我遇到了同样的问题 - 使用 position = "stack" 似乎我们无法在不取消堆叠的情况下分配 width 参数。

但事实证明，这个解决方案非常简单——我们可以使用geom_rect()“手动”构建这样的情节。

有你的数据：

df <- data.frame(
  procedure   = rep(paste("method", 1:4), times = 3),
  sector      = rep(c("construction", "delivery", "service"), each = 4),
  amount      = c(100, 20, 10, 80, 75, 80, 50, 20, 20, 25, 10, 4),
  amount_mean = c(1, 1.2, 0.2, 0.5, 1.3, 0.8, 1.5, 1, 0.8, 0.6, 0.2, 0.9)
)

起初我已经转换了你的数据集：

df <- df |>
  mutate(
      amount_mean = amount_mean / max(amount_mean),
      sector_num  = as.numeric(sector)
  ) |>
  arrange(desc(amount_mean)) |>
  group_by(sector) |>
  mutate(
    xmin = sector_num - amount_mean / 2,
    xmax = sector_num + amount_mean / 2,
    ymin = cumsum(lag(amount, default = 0)), 
    ymax = cumsum(amount)
  ) |>
  ungroup()

我在这里做什么：

1. 我缩小了amount_mean，所以0 >= amount_mean <= 1（更适合绘图，反正我们没有其他比例来显示amount_mean 的真实值）；
2. 我还将sector 变量解码为数值（用于绘图，见下文）；
3. 我已按amount_mean 的降序排列数据集（重表示 - 在底部，轻表示在顶部）；
4. 按部门分组，我计算了xmin、xmax 来表示amount_mean，以及ymin、ymax 的金额。前两个有点棘手。 ymax 很明显 - 您只需从第一个 amount 开始计算所有 amount 的累积和。您还需要累计和来计算ymin，但从0开始。所以第一个矩形用ymin = 0 绘制，第二个矩形用ymin = ymax 绘制，等等。所有这些都是在sectors 的每个单独组中执行的。

绘制数据：

df |>
  ggplot(aes(xmin = xmin, xmax = xmax,
             ymin = ymin, ymax = ymax, 
             fill = procedure
             )
         ) +
  geom_rect() +
  scale_x_continuous(breaks = df$sector_num, labels = df$sector) +
  #ggthemes::theme_tufte() +
  theme_bw() +
  labs(title = "Question 51136471", x = "Sector", y = "Amount") +
  theme(
    axis.ticks.x = element_blank()
  )

结果：

防止对procedure 变量重新排序的另一个选项。所以所有人都可以说“红色”在下降，“绿色”在上面等等。但它看起来很丑：

df <- df |>
  mutate(
      amount_mean = amount_mean / max(amount_mean),
      sector_num = as.numeric(sector)
  ) |>
  arrange(procedure, desc(amount), desc(amount_mean)) |>
  group_by(sector) |>
  mutate(
    xmin = sector_num - amount_mean / 2,
    xmax = sector_num + amount_mean / 2,
    ymin = cumsum(lag(amount, default = 0)), 
    ymax = cumsum(amount)
  ) |>
  ungroup()