ggplot 中不同宽度的堆积条形图

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

接下来，您将找到我的可重现数据：

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。

这是我最终想要的（不是基于上述数据）：

知道如何解决我的问题吗？

我也尝试过同样的情况geom_col()以及，但我也遇到了同样的问题 - 与position = "stack"看来我们不能分配width参数无需拆栈。

但事实证明，这个解决方案非常简单——我们可以使用geom_rect()“手工”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)
)

首先我转换了你的数据集：

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. 我缩小了规模amount_mean， 所以0 >= amount_mean <= 1（更适合绘图，无论如何我们没有另一个比例来显示真实值amount_mean);
2. 我也解码了sector变量转换为数值（用于绘图，见下文）；
3. 我已按降序排列数据集amount_mean (沉重的手段- 在底部，光的意思是在顶端）;
4. 按部门分组，我计算了xmin, xmax来代表amount_mean, and ymin, ymax对于金额。前两者有点棘手。ymax很明显 - 你只需采取累计总和对全部amount从第一个开始。你需要累计总和计算ymin也一样，但是从0开始。所以第一个矩形绘制为ymin = 0, 第二个 - 与ymin = ymax前一个三角形等。所有这些都是在每个单独的组中执行的sectors.

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()
  )

Result:

防止的另一种选择procedure要重新排序的变量。所以都说“红色”在下面，“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()