问题

这是您要翻译的内容：

我有以下形式的数据：

data = 

|组   |条件    |数值       |来源        |
|------|---------|-----------|------------|
| A    |健康     |1.0000000  |模拟        |
| B    |健康     |1.0000000  |模拟        |
| C    |健康     |1.0000000  |模拟        |
| A    |疾病     |0.4589925  |模拟        |
| B    |疾病     |1.4905422  |模拟        |
| C    |疾病     |1.3422035  |模拟        |
| A    |健康     |1.0000000  |实验        |
| B    |健康     |1.0000000  |实验        |
| C    |健康     |1.0000000  |实验        |
| A    |疾病     |0.5158371  |实验        |
| A    |疾病     |0.7559055  |实验        |
| B    |疾病     |1.4153005  |实验        |
| B    |疾病     |1.4000000  |实验        |
| C    |疾病     |1.3300971  |实验        |
| C    |疾病     |1.0000000  |实验        |

我想制作一个堆叠图。沿X轴是组（3个），沿Y轴是值。每个组应该有两个条（一个用于健康，一个用于疾病）。此外，我尝试在上面叠加一个点图，显示我的实验值。

当每个条件只有一个实验值时，我成功地使用以下方法做到了：

`pivoted <- data %>%
    pivot_wider(names_from = Source)`

`ggplot(pivoted, aes(x = group, fill = condition)) +
    geom_col(aes(y = Simulated), position = position_dodge()) +
    labs(x = "组", y = "数值") +
    geom_point(aes(y = Experimental), position = position_dodge(width = 0.9), size = 3)`

然而，现在有重复的情况，这种方法不起作用。

非常感谢您的帮助！

请注意，上述内容已经被翻译成中文，只包括代码部分的英文内容。

答案1

得分: 0

在这种情况下，我建议对您的数据进行子集选择，而不是进行数据透视：

ggplot(data, aes(x = group, y = value, fill = condition)) +
  geom_col(data = filter(data, Source == "Simulated"),
           position = position_dodge()) +
  geom_point(
    data = filter(data, Source == "Experimental"),
    aes(group = condition),
    position = position_dodge(width = 1)
  )

使用此数据：

data = read.table(text = 'group 	condition 	value 	Source
A 	Health 	1.0000000 	Simulated
B 	Health 	1.0000000 	Simulated
C 	Health 	1.0000000 	Simulated
A 	Disease 	0.4589925 	Simulated
B 	Disease 	1.4905422 	Simulated
C 	Disease 	1.3422035 	Simulated
A 	Health 	1.0000000 	Experimental
B 	Health 	1.0000000 	Experimental
C 	Health 	1.0000000 	Experimental
A 	Disease 	0.5158371 	Experimental
A 	Disease 	0.7559055 	Experimental
B 	Disease 	1.4153005 	Experimental
B 	Disease 	1.4000000 	Experimental
C 	Disease 	1.3300971 	Experimental
C 	Disease 	1.0000000 	Experimental', header = T)

ggplot(data, aes(x = group, y = value, fill = condition)) +
  geom_col(data = filter(data, Source == "Simulated"),
           position = position_dodge()) +
  geom_point(
    data = filter(data, Source == "Experimental"),
    aes(group = condition),
    position = position_dodge(width = 1)
  )

data = read.table(text = 'group 	condition 	value 	Source
A 	Health 	1.0000000 	Simulated
B 	Health 	1.0000000 	Simulated
C 	Health 	1.0000000 	Simulated
A 	Disease 	0.4589925 	Simulated
B 	Disease 	1.4905422 	Simulated
C 	Disease 	1.3422035 	Simulated
A 	Health 	1.0000000 	Experimental
B 	Health 	1.0000000 	Experimental
C 	Health 	1.0000000 	Experimental
A 	Disease 	0.5158371 	Experimental
A 	Disease 	0.7559055 	Experimental
B 	Disease 	1.4153005 	Experimental
B 	Disease 	1.4000000 	Experimental
C 	Disease 	1.3300971 	Experimental
C 	Disease 	1.0000000 	Experimental', header = T)