R 绘制连接点集的线段

我试着在x的每一层，在每一个方面，连接两个点的集合。以下是一个可复制的示例：

datum <- structure(list(frequency = c(8L, 7L, 6L, 18L, 5L, 11L, 16L, 15L, 
9L, 8L, 8L, 10L, 2L, 20L, 14L, 3L, 6L, 2L, 2L, 11L, 10L, 6L, 
15L, 19L, 18L, 18L, 8L, 2L, 10L, 15L, 12L, 17L, 1L, 18L, 7L, 
8L, 16L, 4L, 9L, 2L, 7L, 3L, 16L, 7L, 18L, 20L, 9L, 10L, 13L, 
2L, 15L, 7L, 3L, 20L, 4L, 15L, 5L, 7L, 9L, 16L, 5L, 8L, 10L, 
10L, 7L, 10L, 10L, 17L, 7L, 8L, 13L, 13L, 16L, 5L, 20L, 18L, 
13L, 19L, 3L, 8L, 14L, 12L, 20L, 2L, 9L, 13L, 7L, 2L, 5L, 5L, 
13L, 9L, 13L, 7L, 9L, 4L, 4L, 20L, 1L, 4L), band = structure(c(2L, 
4L, 2L, 3L, 2L, 1L, 4L, 1L, 2L, 1L, 3L, 4L, 2L, 4L, 3L, 4L, 3L, 
2L, 3L, 2L, 2L, 4L, 2L, 1L, 1L, 2L, 1L, 4L, 4L, 1L, 4L, 4L, 2L, 
1L, 4L, 4L, 3L, 4L, 1L, 1L, 3L, 4L, 1L, 3L, 4L, 1L, 2L, 1L, 1L, 
2L, 2L, 1L, 3L, 4L, 2L, 1L, 2L, 4L, 2L, 2L, 4L, 4L, 2L, 4L, 4L, 
1L, 1L, 4L, 2L, 3L, 4L, 1L, 2L, 4L, 1L, 2L, 4L, 1L, 1L, 3L, 4L, 
4L, 2L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 3L, 4L, 3L, 3L, 
1L, 3L, 4L), .Label = c("1", "2", "3", "4"), class = "factor"), 
test = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 
2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 
1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 
2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L
), .Label = c("1", "2"), class = "factor"), knowledge = structure(c(2L, 
3L, 1L, 3L, 1L, 1L, 3L, 3L, 1L, 3L, 1L, 3L, 2L, 2L, 1L, 1L, 
1L, 1L, 3L, 3L, 1L, 2L, 3L, 1L, 1L, 2L, 2L, 1L, 1L, 3L, 2L, 
3L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 2L, 3L, 
3L, 2L, 2L, 3L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 1L, 1L, 2L, 
1L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 3L, 2L, 2L, 1L, 2L, 3L, 2L, 
1L, 2L, 3L, 3L, 2L, 1L, 3L, 1L, 3L, 2L, 1L, 3L, 2L, 2L, 3L, 
1L, 1L, 2L, 1L, 2L, 3L, 1L, 3L, 1L), .Label = c("1", "2", 
"3"), class = "factor")), .Names = c("frequency", "band", 
"test", "knowledge"), row.names = c(NA, -100L), class = "data.frame")

查看图中最左侧的面（“1”），我希望在“无”列中有一条线连接前测到后测，在“格式”列中有一条线连接前测到后测，在“含义”列中有一条线连接前测到后测。我希望在每个方面都这样做

---

我希望这是有道理的，谢谢

我发现过分依赖ggplot进行数据操作/汇总可能弊大于利。我不知道如何将位置闪避点与直线连接起来。相反，我会这样做：

library(dplyr)
datsum = datum %>%
  group_by(band, knowledge, test) %>%
  summarize(mean = mean(frequency)) %>%
  ungroup %>%
  mutate(knowledge_fac = factor(knowledge, labels = c('none', 'form', 'meaning')))

ggplot(datsum, aes(x = test, y = mean)) +
  geom_path(aes(group = band:knowledge)) +
  geom_point(aes(color = factor(test))) +
  facet_grid(band ~ knowledge_fac) +
  labs(y='number of words (max = 20)', x='self-report knowledge')

---

借用Gregor在munging数据方面的工作，我认为这符合要求。mutate（）区块将测试创建为数字偏移量，测试1为-0.1，测试2为0.1。然后将其添加到知识的数值中。结果是传递给ggplot2的数字x。Gregor正确地定义了这些组，因此其余的都很简单

library(dplyr)
datsum <-  datum %>%
  group_by(band, knowledge, test) %>%
  summarize(mean = mean(frequency)) %>%
  mutate(Test = 0.1 * (2 * (test == 2) - 1),
         Knowledge = as.numeric(knowledge) + Test) %>%
  ungroup 

ggplot(datsum, aes(x = Knowledge, y = mean, color = test)) +
  geom_path(aes(group = band:knowledge), color = "black") +
  geom_point(size = 3) +
  facet_wrap(~ band, nrow = 1) +
  labs(y='number of words (max = 20)', x='self-report knowledge') +
  scale_color_manual(values = c("orange", "blue")) +
  scale_x_continuous(limits = c(0.5, 3.5), breaks = 1:3, 
                     labels = c("none", "form", "meaning"))

库（dplyr）
datsum%
组别（组别、知识、考试）%>%
汇总（平均值=平均值（频率））%>%
变异（测试=0.1*（2*（测试=2）-1），
知识=数字（知识）+测试%>%
解组
ggplot（数据和，aes（x=知识，y=平均值，颜色=测试））+
几何路径（aes（组=波段：知识），颜色=“黑色”）+
几何点（尺寸=3）+
端面缠绕（~band，nrow=1）+
实验室（y=”字数（最大值=20）”，x=”自我报告知识“）+
比例\颜色\手册（值=c（“橙色”、“蓝色”））+
比例x连续（极限=c（0.5,3.5），断裂=1:3，
标签=c（“无”、“形式”、“意义”））

非常感谢您的帮助。我想我不应该像以前那样依赖ggplot，所以谢谢你的确认。我会将此标记为已解决，即使用线连接位置闪避点的问题尚未解决。@Tjuggles谢谢。是的，如果你想学习如何做到这一点，你应该问一个问题，这个问题在标题中的什么位置，它对于这个问题来说是最小的（简单的模拟数据，没有刻面或其他复杂问题）。

library(dplyr)
datsum <-  datum %>%
  group_by(band, knowledge, test) %>%
  summarize(mean = mean(frequency)) %>%
  mutate(Test = 0.1 * (2 * (test == 2) - 1),
         Knowledge = as.numeric(knowledge) + Test) %>%
  ungroup 

ggplot(datsum, aes(x = Knowledge, y = mean, color = test)) +
  geom_path(aes(group = band:knowledge), color = "black") +
  geom_point(size = 3) +
  facet_wrap(~ band, nrow = 1) +
  labs(y='number of words (max = 20)', x='self-report knowledge') +
  scale_color_manual(values = c("orange", "blue")) +
  scale_x_continuous(limits = c(0.5, 3.5), breaks = 1:3, 
                     labels = c("none", "form", "meaning"))