ggplot2 - 不同宽度的堆积条答案

【问题标题】：ggplot2 - Stacked bar with different widthggplot2 - 不同宽度的堆积条
【发布时间】：2017-08-15 10:49:52
【问题描述】：

我想制作一个反向金字塔图，其中条形以不同的宽度相互堆叠。

第一，我有一个堆积条形图，如下代码示例

library(dplyr)
library(ggplot2)
sample <- data_frame(x=c(1, 1, 1, 1, 2, 2, 2, 2),
                     y=c(5,10,15, 20, 10, 5, 20, 10),
                     w=c(1, 2, 3, 4, 1, 2, 3, 4),
                     group=c("a", "b", "c", "d", "a", "b", "c", "d"))

ggplot() +
    geom_bar(data=sample,
             aes(x=x,y=y,group=group, fill=group),
             stat="identity", position=position_stack())

然后我将宽度添加到aes，因此具有较低w 值的宽度会更小，而它们仍然相互堆叠。但是，条形图上并没有警告。

ggplot() +
geom_bar(data=sample,
         aes(x=x,y=y,group=group, fill=group, width=w/5),
         stat="identity", position=position_stack())

Warning: Ignoring unknown aesthetics: width
Warning message:
position_stack requires non-overlapping x intervals

任何有助于使条形图堆叠或可以涵盖类似概念的不同情节类型的想法将不胜感激。谢谢！

【问题讨论】：

标签： r ggplot2 graph

【解决方案1】：

这有点小技巧。

我将使用geom_rect() 而不是真正的列。因此，我需要使用预先计算好的矩形边界位置创建data.frame()。

df_plot <- sample %>% 
  arrange(desc(group)) %>% # Order so lowest 'groups' firtst
  group_by(x) %>% 
  mutate(yc = cumsum(y), # Calculate position of "top" for every rectangle
         yc2 = lag(yc, default = 0) ,# And position of "bottom"
         w2 = w/5) # Small scale for width


# Plot itself

ggplot(df_plot) +
  geom_rect(
    aes(xmin = x - w2 / 2, xmax = x + w2 / 2,
        ymin = yc, ymax = yc2,
        group = group, fill=group))

结果图：

【讨论】：

【解决方案2】：

带有丝带的较长版本

library(dplyr)
library(ggplot2)
sample <- data_frame(x=c(1, 1, 1, 1, 2, 2, 2, 2),
                     y=c(5,10,15, 20, 10, 5, 20, 10),
                     w=c(1, 2, 3, 4, 1, 2, 3, 4),
                     group=c("a", "b", "c", "d", "a", "b", "c", "d"))

# make factors for non-numeic items
sample$x <- factor(sample$x)
sample$group <- factor(sample$group)

# calcualte cumulative sums
sample2 <- sample %>%
  group_by(x) %>%
  arrange(desc(group)) %>%
  mutate(ycum=cumsum(y)) %>%
  ungroup()  %>%
  select(x, group, ycum, w) 

# Ffor each point, make another row lagged  
sample2lead <- sample2 %>%
  group_by(x) %>%
  mutate(ycum = lag(ycum, default=0), w=lag(w, default=max(sample2$w))) %>%
  ungroup() %>%
  select(x, group, ycum, w) 

# combine   
combined <- bind_rows(sample2, sample2lead) %>%
  arrange(x, ycum, desc(group))


# plot a ribbon forming trapezoids
ggplot() +
  geom_ribbon(data=combined,
             aes(x=ycum, ymin=-w/2, ymax=w/2, fill=group)) +
  coord_flip() +
  facet_grid(~x)

【讨论】：