ggplot2盒须图:显示95%置信区间&删除异常值 [英] ggplot2 box-whisker plot: show 95% confidence intervals & remove outliers
问题描述
我想要一个盒子情节,看起来就像下面的情节。但不是缺省值,我想提出(1)95%置信区间和(2)没有异常值。
95%的置信区间可能意味着(i)延长盒子和除去胡须,或者(ii)只有一个胡须和胡须,然后取出盒子。或者如果人们有其他想法在这样的情节中呈现95%的置信区间,我愿意提供建议。最终目标是显示同一图上多个类别数据的平均值和conf间隔。
set.seed(1234)
df < - data.frame(cond = factor(rep(c(A,B),each = 200)),
rating = c(rnorm(200),rnorm 200,mean = .8))
ggplot(df,aes(x = cond,y = rating,fill = cond))+ geom_boxplot()+
guides(fill = FALSE)+ coord_flip()
图片和源代码: http://www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)/
您可以将大小设置为0来隐藏异常值:
ggplot(df,aes (x = cond,y = rating,fill = cond))+
geom_boxplot(outlier.size = 0)+
guides(fill = FALSE)+ coord_flip()
您可以使用 stat_summary
函数将平均值添加到图中:
$ b $
ggplot(df,aes(x = cond,y = rating,fill = cond))+
geom_boxplot(outlier.size = 0)+
stat_summary(fun.y =mean,geom =point,shape = 23,size = 4,fill =white)+
guides(fill = FALSE)+
coord_flip()
I'd like a box plot that looks just like the one below. But instead of the default, I'd like to present (1) 95% confidence intervals and (2) without the outliers.
The 95% confidence intervals could mean (i) extending the boxes and removing the whiskers, or (ii) having just a mean and whiskers, and removing the boxes. Or if people have other ideas for presenting 95% confidence intervals in a plot like this, I'm open to suggestions. The final goals is to show mean and conf intervals for data across multiple categories on the same plot.
set.seed(1234)
df <- data.frame(cond = factor( rep(c("A","B"), each=200) ),
rating = c(rnorm(200),rnorm(200, mean=.8))
ggplot(df, aes(x=cond, y=rating, fill=cond)) + geom_boxplot() +
guides(fill=FALSE) + coord_flip()
Image and code source: http://www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)/
You can hide the outliers by setting the size to 0:
ggplot(df, aes(x=cond, y=rating, fill=cond)) +
geom_boxplot(outlier.size = 0) +
guides(fill=FALSE) + coord_flip()
You can add the mean to the plot with the stat_summary
function:
ggplot(df, aes(x=cond, y=rating, fill=cond)) +
geom_boxplot(outlier.size = 0) +
stat_summary(fun.y="mean", geom="point", shape=23, size=4, fill="white") +
guides(fill=FALSE) +
coord_flip()
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