Removing points from plot generated with stat_summary - r

Question

I've been asked to remove points from a plot that I've made with ggplot2. I'm attaching a MWE:
require(ggplot2)
require(Hmisc)
x = 5
k = 50
kx = k*5
data.A.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 0)
data.B.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 1)
data.C.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 2)
data.A.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 3)
data.B.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 4)
data.C.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 5)
multiple.plot.6x3.interval <- function(D, L) {
data = data.frame()
# join all the data in D into 'data'
e = 0
NN = ""
for (i in seq(1, length(D))) {
lidx = i%%3
if (lidx == 0) { lidx = 3 }
if (lidx == 1) {
e = e + 1
NN = paste0("10^", e)
}
n.obs = length(D[[i]]$n)
D[[i]]$lang.name = rep(L[lidx], n.obs)
D[[i]]$N = rep(NN, n.obs)
data = rbind(data, D[[i]])
}
# make the plot
g <- ggplot(data, aes(x=n, y=v)) +
stat_summary( # plot confidence interval
fun.data = mean_cl_boot, fun.args = (conf.int = 0.99),
geom = "ribbon", fill = "darkgrey"
) +
stat_summary( # plot maximum and minimum bars
fun = mean, fun.min = min, fun.max = max,
colour = "red", size = 0.15
) +
stat_summary(
fun = mean,
geom = "line", linetype = "solid", size = 0.4, color = "black"
) +
coord_cartesian(xlim=c(1, 100)) +
scale_x_continuous(breaks=seq(1, 101, 10)-1) +
facet_grid(
N ~ lang.name, labeller = "label_parsed"
) +
labs(
x=bquote("X"),
y=bquote("Y")
) +
theme(text = element_text(size = 20))
return (g)
}
g <- multiple.plot.6x3.interval(
list(
data.A.1, data.B.1, data.C.1,
data.A.2, data.B.2, data.C.2
),
c("A", "B", "C")
)
plot(g)
The result of this code is the one I want, but with the exception that I've been asked to remove the points that this
stat_summary( # plot maximum and minimum bars
fun = mean, fun.min = min, fun.max = max,
colour = "red", size = 0.15
) +
generates while keeping the bars.
This is what I get, and I would like to remove the red points (not the red bars).
Using size = 0 will make the bars completely invisible. I haven't been able to do this myself. I wonder: can this be done? If so, how? Any help will be appreciated.
Thank you all.

Answer 1

Try geom = "errorbar" as an argument to stat_summary:
require(ggplot2)
require(Hmisc)
x = 5
k = 50
kx = k*5
data.A.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 0)
data.B.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 1)
data.C.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 2)
data.A.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 3)
data.B.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 4)
data.C.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 5)
multiple.plot.6x3.interval <- function(D, L) {
data = data.frame()
# join all the data in D into 'data'
e = 0
NN = ""
for (i in seq(1, length(D))) {
lidx = i%%3
if (lidx == 0) { lidx = 3 }
if (lidx == 1) {
e = e + 1
NN = paste0("10^", e)
}
n.obs = length(D[[i]]$n)
D[[i]]$lang.name = rep(L[lidx], n.obs)
D[[i]]$N = rep(NN, n.obs)
data = rbind(data, D[[i]])
}
# make the plot
g <- ggplot(data, aes(x=n, y=v)) +
stat_summary( # plot confidence interval
fun.data = mean_cl_boot, fun.args = (conf.int = 0.99),
geom = "ribbon", fill = "darkgrey"
) +
stat_summary( # plot maximum and minimum bars
fun = mean, fun.min = min, fun.max = max,
geom = "errorbar", ### HERE
colour = "red", size = 0.15
) +
stat_summary(
fun = mean,
geom = "line", linetype = "solid", size = 0.4, color = "black"
) +
coord_cartesian(xlim=c(1, 100)) +
scale_x_continuous(breaks=seq(1, 101, 10)-1) +
facet_grid(
N ~ lang.name, labeller = "label_parsed"
) +
labs(
x=bquote("X"),
y=bquote("Y")
) +
theme(text = element_text(size = 20))
return (g)
}
g <- multiple.plot.6x3.interval(
list(
data.A.1, data.B.1, data.C.1,
data.A.2, data.B.2, data.C.2
),
c("A", "B", "C")
)
plot(g)