如何突出显示不在数据中的点？

Question

我要突出显示某些点，但这不在原始数据集中。

假设我正在使用此数据集。

library(gcookbook) # To use 'heightweight' dataset
head(heightweight)
  sex ageYear ageMonth heightIn weightLb
1   f   11.92      143     56.3     85.0
2   f   12.92      155     62.3    105.0
3   f   12.75      153     63.3    108.0
4   f   13.42      161     59.0     92.0
5   f   15.92      191     62.5    112.5
6   f   14.25      171     62.5    112.0
ggplot(heightweight, aes(x = ageYear, y = heightIn, color = sex)) + geom_point()

ggplot 到这里为止没有问题，但我想强调每个组（性别）的均值。

female = subset(heightweight, select = c(ageYear, heightIn), subset = (sex == 'f'))
male = subset(heightweight, select = c(ageYear, heightIn), subset = (sex == 'm'))
female_a = mean(female[,1]); female_a
[1] 13.70063
female_h = mean(female[,2]); female_h
[1] 60.52613
male_a = mean(male[,1]); male_a
[1] 13.64752
male_h = mean(male[,2]); male_h
[1] 62.06

很显然，这些点不在数据集中，但是我想用粗点突出显示原始ggplot中的这些点。

有什么想法吗？

Answer 1

一种方法是在数据集中进行预先计算：

heightweight <- heightweight %>%
  group_by(sex) %>%
  mutate(
    ageyear = mean(ageYear),
    heightin = mean(heightIn)
  ) %>% ungroup()

剧情：

ggplot(heightweight, aes(x = ageYear, y = heightIn, color = sex)) + 
  geom_point() + 
  geom_point(aes(x = ageyear, y = heightin), size = 5)

这可能是管道的一部分，例如：

heightweight %>%
  group_by(sex) %>%
  mutate(
    ageyear = mean(ageYear),
    heightin = mean(heightIn)
  ) %>% ungroup() %>%
  ggplot(aes(x = ageYear, y = heightIn, color = sex)) + 
  geom_point() + 
  geom_point(aes(x = ageyear, y = heightin), size = 5)

此方法的优势在于，它节省了一些编码时间/空间，并且您无需转换（例如，从base到ggplot2），并且颜色自动与其他点（由sex分隔）。

我只是增加了您希望看到的mean点的大小。当然，可能会有进一步的调整，具体取决于您希望如何绘制数据。

Answer 2

您可以这样做：

 plot_missing_mean_value =    ggplot(heightweight, aes(x = ageYear, y = heightIn, color = sex)) + geom_point()+
      geom_point(aes(female_a, female_h,size = 5), colour="blue")+
      geom_point(aes(male_a, male_h,size = 5), colour="green")

Answer 3

类似于@ arg0naut，但避免了一系列重叠的意思：

RELATION_ID
SOURCE_1
ACCOUNT_1
ENTITY_ID_1 (ENTITY_ID (from ACCOUNTS table) related to SOURCE_1 and ACCOUNT_1)
SOURCE_2
ACCOUNT_2
ENTITY_ID_2 (ENTITY_ID (from ACCOUNTS table) related to SOURCE_2 and ACCOUNT_2)