Just in case someone hits this question with ggplot
's geom_histogram
in mind, note that there is a way to extract the data from a ggplot object.
The following convenience function outputs a dataframe with the lower limit of each bin (xmin
), the upper limit of each bin (xmax
), the mid-point of each bin (x
), as well as the frequency value (y
).
## Convenience function
get_hist <- function(p) {
d <- ggplot_build(p)$data[[1]]
data.frame(x = d$x, xmin = d$xmin, xmax = d$xmax, y = d$y)
}
# make a dataframe for ggplot
set.seed(1)
x = runif(100, 0, 10)
y = cumsum(x)
df <- data.frame(x = sort(x), y = y)
# make geom_histogram
p <- ggplot(data = df, aes(x = x)) +
geom_histogram(aes(y = cumsum(..count..)), binwidth = 1, boundary = 0,
color = "black", fill = "white")
Illustration:
hist = get_hist(p)
head(hist$x)
## [1] 0.5 1.5 2.5 3.5 4.5 5.5
head(hist$y)
## [1] 7 13 24 38 52 57
head(hist$xmax)
## [1] 1 2 3 4 5 6
head(hist$xmin)
## [1] 0 1 2 3 4 5
A related question I answered here (Cumulative histogram with ggplot2).