制作一个堆叠的区域图，每个组都整齐地放在另一个组的上面。

Question

数据帧在下面。我试图创建一个堆叠的区域图，其中每个组被堆叠，一个在另一个上面。

下面是我目前所掌握的问题：

example_df %>% group_by(NEW_REG_DATE, CARD_TYPE) %>% summarise(Count = n()) %>%
  ggplot(aes(x = NEW_REG_DATE, y = Count, fill = CARD_TYPE, group = CARD_TYPE)) +
  geom_area(alpha = 0.4) +
  stat_summary(aes(group = 2), fun.y = sum, geom = 'line', size = 2, alpha = 0.5) +
  scale_x_date(date_labels = "%d-%b", date_breaks = "1 week", expand = c(0, 0)) +
  theme(axis.text.x=element_text(angle=90,hjust=1), legend.position = "bottom")

以下是它的外观：

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注意，这些组看起来好像是重叠的，很难区分每个组。我想把它们整齐地叠在一起。我怎么能这么做？

以下是数据：

example_df <- structure(list(NEW_REG_DATE = structure(c(16806, 16792, 16792, 
16802, 16826, 16882, 16779, 16783, 16876, 16779, 16822, 16835, 
16802, 16815, 16823, 16867, 16801, 16872, 16800, 16823, 16868, 
16792, 16779, 16853, 16773, 16877, 16820, 16866, 16783, 16779, 
16835, 16832, 16847, 16870, 16872, 16847, 16862, 16854, 16792, 
16893, 16781, 16812, 16816, 16851, 16791, 16867, 16771, 16865, 
16785, 16857, 16787, 16813, 16830, 16849, 16785, 16873, 16856, 
16770, 16810, 16822, 16782, 16877, 16841, 16777, 16865, 16841, 
16830, 16827, 16789, 16850, 16768, 16796, 16784, 16785, 16784, 
16831, 16815, 16853, 16845, 16865, 16770, 16878, 16878, 16789, 
16788, 16796, 16791, 16808, 16814, 16853, 16792, 16820, 16785, 
16770, 16847, 16772, 16810, 16864, 16810, 16800, 16822, 16861, 
16830, 16775, 16810, 16822, 16771, 16826, 16773, 16886, 16777, 
16779, 16867, 16866, 16814, 16859, 16775, 16791, 16809, 16808, 
16871, 16774, 16868, 16791, 16792, 16835, 16848, 16787, 16877, 
16783, 16775, 16822, 16788, 16793, 16793, 16790, 16802, 16796, 
16820, 16779, 16810, 16866, 16783, 16842, 16785, 16772, 16821, 
16794, 16779, 16862, 16802, 16877, 16798, 16802, 16787, 16862, 
16877, 16812, 16800, 16787, 16826, 16868), class = "Date"), CARD_TYPE = c("Youth", 
"Youth", "Youth with Parent", "Youth with Parent", "Youth with Parent", 
"Adult", "Youth", "Youth with Parent", "Youth with Parent", "Youth", 
"Youth with Parent", "Youth", "Youth with Parent", "Youth", "Youth with Parent", 
"Youth", "Youth", "Youth", "Youth", "Youth", "Youth", "Youth with Parent", 
"Youth with Parent", "Youth", "Youth", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth", "Youth", "Youth", "Youth", "Youth with Parent", 
"Youth", "Youth with Parent", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth", "Adult", "Youth with Parent", "Youth with Parent", 
"Youth with Parent", "Youth with Parent", "Youth", "Youth", "Youth", 
"Youth", "Youth", "Youth with Parent", "Youth with Parent", "Youth with Parent", 
"Youth with Parent", "Youth", "Youth with Parent", "Youth", "Youth with Parent", 
"Youth with Parent", "Youth", "Youth", "Youth", "Youth", "Youth with Parent", 
"Adult", "Youth with Parent", "Youth with Parent", "Youth", "Youth with Parent", 
"Youth", "Youth", "Adult", "Youth", "Youth", "Youth with Parent", 
"Youth with Parent", "Youth", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth", "Youth with Parent", "Youth with Parent", "Youth", 
"Youth with Parent", "Youth", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth", "Youth", "Youth", "Youth", "Youth with Parent", 
"Youth", "Youth", "Youth", "Youth", "Youth", "Youth", "Youth", 
"Youth", "Youth with Parent", "Youth", "Youth", "Youth", "Youth", 
"Youth", "Youth", "Youth with Parent", "Youth with Parent", "Youth", 
"Youth", "Youth with Parent", "Youth with Parent", "Youth", "Youth", 
"Youth", "Youth", "Youth", "Youth with Parent", "Youth", "Youth", 
"Youth with Parent", "Youth", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth", "Youth with Parent", "Youth with Parent", "Youth with Parent", 
"Youth", "Youth with Parent", "Youth", "Youth", "Youth", "Youth with Parent", 
"Youth with Parent", "Youth with Parent", "Youth", "Youth", "Youth", 
"Youth", "Youth", "Youth", "Youth with Parent", "Adult", "Youth", 
"Youth with Parent", "Youth", "Youth", "Youth", "Youth", "Youth", 
"Youth", "Youth", "Youth with Parent", "Youth", "Youth with Parent", 
"Youth with Parent", "Youth", "Youth with Parent")), class = "data.frame", row.names = c(NA, 
-162L), .Names = c("NEW_REG_DATE", "CARD_TYPE"))

Answer 1

您的代码是可以工作的，但是很明显，问题在于数据中缺少大量的(NEW_REG_DATE, CARD_TYPE)组合。下面我使用tidyr添加那些Count为0的缺失组合：

library(tidyr)
example_df$CARD_TYPE <- factor(example_df$CARD_TYPE)
example_df %>% group_by(NEW_REG_DATE, CARD_TYPE) %>% summarise(Count = n()) %>%
  complete(NEW_REG_DATE, CARD_TYPE, fill = list(Count = 0)) %>%
  ggplot(aes(x = NEW_REG_DATE, y = Count)) +
  geom_area(aes(fill = CARD_TYPE), alpha = 0.4) +
  stat_summary(aes(group = 2), fun.y = sum, geom = 'line', size = 2, alpha = 0.5) +
  scale_x_date(date_labels = "%d-%b", date_breaks = "1 week", expand = c(0, 0)) +
  theme(axis.text.x = element_text(angle = 90, hjust = 1), legend.position = "bottom")

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