library(ggplot2)
data = diamonds[, c(\'carat\', \'color\')]
data = data[data$color %in% c(\'D\', \'E\'), ]
I would like to compare the histogram of
It seems that binning the data outside of ggplot2 is the way to go. But I would still be interested to see if there is a way to do it with ggplot2.
library(dplyr)
breaks = seq(0,4,0.5)
data$carat_cut = cut(data$carat, breaks = breaks)
data_cut = data %>%
group_by(color, carat_cut) %>%
summarise (n = n()) %>%
mutate(freq = n / sum(n))
ggplot(data=data_cut, aes(x = carat_cut, y=freq*100, fill=color)) + geom_bar(stat="identity",position="dodge") + scale_x_discrete(labels = breaks) + ylab("Percentage") +xlab("Carat")