Welcome to OStack Knowledge Sharing Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
1.0k views
in Technique[技术] by (71.8m points)

r - Let ggplot2 histogram show classwise percentages on y axis

library(ggplot2)
data = diamonds[, c('carat', 'color')]
data = data[data$color %in% c('D', 'E'), ]

I would like to compare the histogram of carat across color D and E, and use the classwise percentage on the y-axis. The solutions I have tried are as follows:

Solution 1:

ggplot(data=data, aes(carat, fill=color)) +  geom_bar(aes(y=..density..), position='dodge', binwidth = 0.5) + ylab("Percentage") +xlab("Carat")

enter image description here

This is not quite right since the y-axis shows the height of the estimated density.

Solution 2:

 ggplot(data=data, aes(carat, fill=color)) +  geom_histogram(aes(y=(..count..)/sum(..count..)), position='dodge', binwidth = 0.5) + ylab("Percentage") +xlab("Carat")

enter image description here

This is also not I want, because the denominator used to calculate the ratio on the y-axis are the total count of D + E.

Is there a way to display the classwise percentages with ggplot2's stacked histogram? That is, instead of showing (# of obs in bin)/count(D+E) on y axis, I would like it to show (# of obs in bin)/count(D) and (# of obs in bin)/count(E) respectively for two color classes. Thanks.

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Answer

0 votes
by (71.8m points)

You can scale them by group by using the ..group.. special variable to subset the ..count.. vector. It is pretty ugly because of all the dots, but here it goes

ggplot(data, aes(carat, fill=color)) +
  geom_histogram(aes(y=c(..count..[..group..==1]/sum(..count..[..group..==1]),
                         ..count..[..group..==2]/sum(..count..[..group..==2]))*100),
                 position='dodge', binwidth=0.5) +
  ylab("Percentage") + xlab("Carat")

enter image description here


与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome to OStack Knowledge Sharing Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...