[英]Normalizing y-axis in histograms in R ggplot to proportion by group
My question is very similar to Normalizing y-axis in histograms in R ggplot to proportion , except that I have two groups of data of different size, and I would like that each proportion is relative to its group size instead of the total size.我的问题与将R ggplot 中直方图中的 y 轴归一化为比例非常相似,除了我有两组不同大小的数据,我希望每个比例都与其组大小有关,而不是总大小。
To make it clearer, let's say I have two sets of data in a data frame:为了更清楚,假设我在一个数据框中有两组数据:
dataA<-rnorm(100,3,sd=2)
dataB<-rnorm(400,5,sd=3)
all<-data.frame(dataset=c(rep('A',length(dataA)),rep('B',length(dataB))),value=c(dataA,dataB))
I can plot the two distributions together with:我可以将这两个分布与:
ggplot(all,aes(x=value,fill=dataset))+geom_histogram(alpha=0.5,position='identity',binwidth=0.5)
and instead of the frequency on the Y axis I can have the proportion with:而不是 Y 轴上的频率,我可以使用以下比例:
ggplot(all,aes(x=value,fill=dataset))+geom_histogram(aes(y=..count../sum(..count..)),alpha=0.5,position='identity',binwidth=0.5)
But this gives the proportion relative to the total data size (500 points here): is it possible to have it relative to each group size?但这给出了相对于总数据大小的比例(此处为 500 分):是否有可能相对于每个组大小?
My goal here is to make it possible to compare visually the proportion of values in a given bin between A and B, independently from their respective size.我的目标是可以直观地比较 A 和 B 之间给定 bin 中的值的比例,独立于它们各自的大小。 Ideas which differ from my original one are also welcome!
也欢迎与我原来的想法不同的想法!
Thanks!谢谢!
Like this?像这样? [edited based on OP's comment]
[根据OP的评论编辑]
ggplot(all,aes(x=value,fill=dataset))+
geom_histogram(aes(y=0.5*..density..),
alpha=0.5,position='identity',binwidth=0.5)
Using y=..density..
scales the histograms so the area under each is 1, or sum(binwidth*y)=1.
使用
y=..density..
缩放直方图,使每个下的面积为 1,或sum(binwidth*y)=1.
As a result, you would use y = binwidth*..density..
to have y represent the fraction of the total in each bin.因此,您将使用
y = binwidth*..density..
来让 y 表示每个 bin 中总数的分数。 In your case, binwidth=0.5
.在您的情况下,
binwidth=0.5
。
IMO this is a little easier to interpret: IMO 这更容易解释:
ggplot(all,aes(x=value,fill=dataset))+
geom_histogram(aes(y=0.5*..density..),binwidth=0.5)+
facet_wrap(~dataset,nrow=2)
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