r - 在ggplot中具有不同宽度的堆叠条形图

Question

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，您会发现我的可重复数据:

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)

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？

Answer 1

我也试过，geom_col()也一样，但我遇到了同样的问题 - position = "stack"似乎我们不能分配一个 width参数没有拆开。

但事实证明，该解决方案非常简单——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)
)

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:

我缩小了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 amount_mean 的真实值)；

我也解码了sector变量转换为数字(用于绘图，见下文)；

我已按 amount_mean 按降序排列数据集(重表示 - 在底部，轻表示在顶部)；

按部门分组，我计算出xmin , xmax代表amount_mean , 和 ymin , ymax为金额。前两个比较麻烦。 ymax很明显 - 您只需为所有 amount 取一个累积总和从第一个开始。您需要累积和来计算 ymin同样，但从 0 开始。所以第一个矩形用 ymin = 0 绘制，第二个 - 与 ymin = ymax以前的三角形等。所有这些都是在 sector 的每个单独组中执行的。 s。

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:



阻止 procedure 的另一种选择要重新排序的变量。所以都可以说“红色”在下方，“绿色”在上方等等。但它看起来很难看:

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()