分类范围中geom_point的position_dodge的垂直等效项

Question

当我有一个明确的y变量时，我想避开垂直重叠的geom_point。

library(tidyverse)
# all possible points
df <- expand.grid(
  y_factor = paste0('factor_',1:5),
  x =1:100
)%>%as.tbl

# randomly missing and overlapping points
# every green point has a pink point underneath, and every blue point 
# has a green point underneath it.
seed<-1
df_with_overlap<-df%>%
  sample_frac(0.5,replace = TRUE)%>%
  group_by(y_factor,x)%>%
  mutate(n=factor(1:n()))
p<-ggplot(data=df_with_overlap, aes(x=x, y=y_factor, col=n))
p+geom_point()

position_dodge由于数据在该轴上过于拥挤，因此无法使用水平躲避，因此某些点仍然重叠并且可视化效果不清晰。

p+geom_point(position=position_dodge(width=1))+
  ggtitle('position_dodge isnt what Im looking for. 
          \nx-axis too crowded and points still overlap')

position_jitter这种工作方式是因为我可以将x抖动限制为0，并控制y抖动的程度。但是，抖动的随机性使其吸引力降低。当它们存在时，我可以区分出三种颜色。

p+geom_point(aes(col=n), position=position_jitter(width=0, height=0.05))+
  ggtitle('Jitter kind of works.
          \nIt would work better if it wasnt random
          \nlike position_dodge, but vertical dodging')

有没有一种方法可以垂直避开点？

Answer 1

感谢@aosmith的建议ggstance::position_dodgev()。这正是我想要的。我增加了过采样，因此效果更加明显。

df <- expand.grid(
  y_factor = paste0('factor_',1:5),
  x =1:100
)%>%as.tbl

seed<-1
df_with_overlap<-df%>%
  sample_frac(1.5,replace = TRUE)%>%
  group_by(y_factor,x)%>%
  mutate(n=factor(1:n()))

ggplot(data=df_with_overlap, aes(x=x, y=y_factor, col=n))+
  geom_point(position=ggstance::position_dodgev(height=0.3))