如何在ggplot中的彩色条形图上层上一个概述的条形图？ 我的数据看起来像这样： Expect_Data resp_migration_status KMCluster 百分比 预期的 1个非移民 1 21.9 30.5 2非移民 2 30.1 27.4 3非移民 3 24.7 19.9 4非移民 ...

Question

resp_migration_status

kmcluster百分点1非移民 30.5230.127.43非移民 423.322.35移民 6移民 222.627.47移民 3416.122.39流离失所 36.9226.227.411流离失所 19.942522.3kmclusterRESP_MIGRATION_STATUS

ggplot(expected_data, aes(x = resp_migration_status, y = percentage, fill = kmcluster)) +
  geom_bar(stat = "identity", position = "dodge") +  # Use stat = "identity" for pre-computed values
  labs(
    title = "Percentage distribution of network cluster by migration status",
    x = "Migration Status",
    y = "Percentage",
    fill = "Cluster"
  ) +
  scale_y_continuous(labels = scales::percent_format(scale = 1)) +  # Format y-axis as percentages
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1)
  )

kmclusterRESP_MIGRATION_STATUS我如何在原始图上覆盖一个非常基本的（黑色概述）条形图？ 我有此代码：

ggplot(expected_data, aes(x = resp_migration_status, y = expected, fill = kmcluster)) +
  geom_bar(stat = "identity", position = "dodge", color = "black", fill = NA) +  # Use stat = "identity" for pre-computed values, bars with black outlines
  labs(
    title = "Expected percentage distribution of network cluster by migration status",
    x = "Migration Status",
    y = "Percentage"
  ) +
  scale_y_continuous(labels = scales::percent_format(scale = 1)) +  # Format y-axis as percentages
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1)
  )

但在geom_bar中添加填充= na覆盖了AES中的填充=群集，因此它不再将数据划分为群集类型，并且可以使其变成一些奇怪的堆积栏（请参阅图像）。

预期
		1	21.9
	2非移民
	3	24.7	19.9
4非移民
1	41.9	30.5
19.4	19.9		8移民
			1
30.5		10流离失所
		3	11.9
	12流离失所
	我想构建一个条形图，该栏图显示了	以及	。 我已经成功地使用此代码完成了此操作：
在此条形图上进行了延误，我想做另一个带有黑色轮廓的图形，该图显示了	和	的the the the the。 本质上，这是卡方检验的图形表示：与“实际”分布相比，与某些迁移类型在一个集群中不成比例的“实际”分布相比，了解群集的分布是什么。

所以第一个问题是： 我如何将数据除以迁移类型和群集，而不在每个栏中着色，而只是用黑色概述它们？

第二：

我如何将此条形图叠加在原始图表上？ 要在必须在group

aes上明确映射的第一个栏的顶部添加第二个栏，以仍然获得躲闪的条形图。

library(ggplot2)

ggplot(expected_data, aes(
  x = resp_migration_status,
  y = percentage, fill = factor(kmcluster)
)) +
  geom_col(position = "dodge") +
  geom_col(aes(y = expected, group = factor(kmcluster)),
    color = "black", fill = NA, position = "dodge"
  ) +
  labs(
    title = "Percentage distribution of network cluster by migration status",
    x = "Migration Status",
    y = "Percentage",
    fill = "Cluster"
  ) +
  scale_y_continuous(labels = scales::percent_format(scale = 1)) + # Format y-axis as percentages
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1)
  )

data

expected_data <- data.frame(
  resp_migration_status = c(
    "Non-migrant", "Non-migrant", "Non-migrant", "Non-migrant",
    "Migrant", "Migrant", "Migrant", "Migrant",
    "Displaced", "Displaced", "Displaced", "Displaced"
  ),
  kmcluster = c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L),
  percentage = c(
    21.9, 30.1, 24.7,
    23.3, 41.9, 22.6, 19.4, 16.1, 36.9, 26.2, 11.9, 25
  ),
  expected = c(
    30.5, 27.4, 19.9,
    22.3, 30.5, 27.4, 19.9, 22.3, 30.5, 27.4, 19.9, 22.3
  )
)