拆分beeswarm 2 [英] Split beeswarm 2

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本文介绍了拆分beeswarm 2的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

这是对最后一个问题的后续追踪:



为什么这会随着样本量的增加而发生??

解决方案

好的,我希望这是值得自我回答的。

它与分配点的方法有关。改变这一点:$ b​​
$ b

  p < -  ggplot(my_dat,aes(x,y,color = m))+ 
geom_quasirandom(method ='pseudorandom')#代替'smiley'

p < - ggplot_build(p)

p $ data [[1]] < - p $ data [[1]]%>%
mutate(x = case_when(
color ==#00BFC4〜PANEL + abs(PANEL-x),
TRUE〜PANEL - abs (PANEL-x))

plot(ggplot_gtable(p))



猜猜我必须阅读更多关于这些方法的信息。

This is a follow up on the last question: Split beeswarm plot

I ask it as a new question, because my first question was sufficiently answered. But with my real data, there was suddenly a weird behaviour that I don't understand.

With the previous data frame

my_dat <- data.frame(x = 'x', m = rep(c('a','b'),100), y = rnorm(200))

the suggested solution works nice. But when I boost up my data a bit (simply increasing the sample size!), the plot becomes weird:

my_dat <- data.frame(x = 'x', m = letters[1:2], y = sample(0:100, 2000, replace = T), stringsAsFactors = F)

require(ggplot2)
require(ggbeeswarm)
require(dplyr)

p <- ggplot(my_dat, aes(x,y,color=m))+  ## this is copy/paste from @Jimbou's great idea. 
  geom_quasirandom(method = 'smiley')

p <- ggplot_build(p)

p$data[[1]] <-   p$data[[1]] %>%
  mutate(x=case_when(
    colour=="#00BFC4" ~ PANEL + abs(PANEL - x),
    TRUE ~ PANEL - abs(PANEL - x))
  )
plot(ggplot_gtable(p))

Why does this happen with increased sample size??

解决方案

Ok, I hope this is worth a self-answer.

It has to do with the method to distribute the points. Changing this:

p <- ggplot(my_dat, aes(x,y,color=m))+  
  geom_quasirandom(method = 'pseudorandom') #instead of 'smiley'

p <- ggplot_build(p)

p$data[[1]] <-   p$data[[1]] %>%
  mutate(x=case_when(
    colour=="#00BFC4" ~ PANEL + abs(PANEL - x),
    TRUE ~ PANEL - abs(PANEL - x))
  )
plot(ggplot_gtable(p))

Guess I have to read more about those methods.

这篇关于拆分beeswarm 2的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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