Using builtin dataset stackloss try this:
f <- function(x) replace(quantile(x, c(5, 25, 50, 75, 95)/100), 3, mean(x))
bxp(list(stats = sapply(stackloss, f), n = stackloss, names = names(stackloss)))
and see ?bxp and ?boxplot
On Feb 17, 2008 9:17 PM, Stropharia <[EMAIL PROTECTED]> wrote:
>
> Any
[EMAIL PROTECTED] wrote in
news:[EMAIL PROTECTED]:
> It's fairly simple to set up something like this for ggplot2:
>
> install.packages("ggplot2")
> library(ggplot2)
>
> library(ggplot2)
>
> q5 <- function(data) {
> q <- function(p) unname(quantile(data$y, p))
> data.frame(min = q(0.05), max
It's fairly simple to set up something like this for ggplot2:
install.packages("ggplot2")
library(ggplot2)
library(ggplot2)
q5 <- function(data) {
q <- function(p) unname(quantile(data$y, p))
data.frame(min = q(0.05), max = q(0.95))
}
ggplot(diamonds, aes(x = cut, y = price)) +
stat_summary(f
Any help with this problem would be greatly appreciated:
I need to produce a custom plot i haven't come across in R. Basically, I
want to show means, 1st standard deviation and 5th and 95th percentiles
visually, using something resembling a boxplot. Is it possible to completely
customize a boxplo
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