how to change the lower and upper point in this stat summary plot to 25% quartile and 75% quartile?
ggplot(data = diamonds) + stat_summary(
mapping = aes(x = cut, y = depth),
fun.ymin = min,
fun.ymax = max,
fun.y = median
)
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3 Answers
ggplot(data = diamonds) + stat_summary(
mapping = aes(x = cut, y = depth),
fun.min = function(z) { quantile(z,0.25) },
fun.max = function(z) { quantile(z,0.75) },
fun = median)
5 Comments
spleen
HI,@DomQ I crossed this answer and it helped me a lot. Can I ask for a clarification? fun.min receives a vector and returns a number, how does function() knows that you are passing Depth. is the dependent variable y being pass by default? Thanks a lot
G5W
@spleen
ggplot will apply fun.min to its y value (which was specified as depth). The default function that is used is min, but defining fun.min like this allows the use of a different function. ggplot knows to apply fun.min to its y value.
tnt
what is z in this answer? I'm trying to adapt this to a slightly different plot, but I have no idea how to specify that the function should be applied to the x value.
G5W
@tnt z is just a placeholder variable. I am defining functions to get the upper and lower limit for the bars in the graph.
tnt
@G5W I can't get this solution to work for me: stackoverflow.com/questions/78208127/…
Rewriting G5W's solution, using the geom function instead of the stat function:
ggplot(data = diamonds) +
geom_pointrange(mapping = aes(x = cut, y = depth),
stat = "summary",
fun.min = function(z) {quantile(z,0.25)},
fun.max = function(z) {quantile(z,0.75)},
fun = median)
Comments
This question already has excellent answers, but I wanted to build on these with more brief solution, as I prefer to keep code for plots short. stat_summary can take custom functions, with support for arguments.
library(ggplot2)
# Define function to calculate IQR at given quantiles
iqr = function(z, lower = 0.25, upper = 0.75) {
data.frame(
y = median(z),
ymin = quantile(z, lower),
ymax = quantile(z, upper)
)
}
# Plot standard IQR
ggplot(data = diamonds, mapping = aes(x = cut, y = depth)) +
stat_summary(fun.data = iqr)
# Arguments can be accessed with fun.args
ggplot(data = diamonds, mapping = aes(x = cut, y = depth)) +
stat_summary(fun.data = iqr, fun.args = list(lower = 0.1, upper = 0.9))
Created on 2022-08-29 by the reprex package (v2.0.0)
