I would like to create multiple plots using for loop setup. However my code does not work. Could anyone give me some guidance on this?
for i in 1:4 {
paste0("p_carb_",i) <- ggplot(mtcars%>% filter(carb==4), aes(x = wt, y = mpg, color = disp))
+ geom_point()
}
Perhaps this?
library(ggplot2)
library(dplyr)
ggs <- lapply(sort(unique(mtcars$carb)), function(crb) {
ggplot(filter(mtcars, carb == crb), aes(x = wt, y = mpg, color = disp)) +
geom_point()
})
This produces six plots, which when the first two are viewed side-by-side (calling ggs[[1]] and then ggs[[2]]), we see
An alternative might be to facet the data, as in
ggplot(mtcars, aes(x = wt, y = mpg, color = disp)) +
facet_wrap(~ carb) +
geom_point()
But the literal translation of your paste(..) <- ... code into something syntactically correct, we'd use an anti-pattern in R: assign:
for (crb in sort(unique(mtcars$carb))) {
gg <- ggplot(filter(mtcars, carb == crb), aes(x = wt, y = mpg, color = disp)) +
geom_point()
assign(paste0("carb_", crb), gg)
}
Again, this is not the preferred/best-practices way of doing things. It is generally considered much better to keep like-things in a list for uniform/consistent processing of them.
Multiple IDs ... two ways:
Nested lapply:
carbs <- sort(unique(mtcars$carb))
ggs <- lapply(carbs, function(crb) {
gears <- subset(mtcars, carb == crb)$gear
lapply(gears, function(gr) {
ggplot(dplyr::filter(mtcars, carb == crb, gear == gr), aes(x = wt, y = mpg, color = disp)) +
geom_point()
})
})
Where ggs[[1]] is a list of lists. ggs[[1]][[1]] will be one plot.
split list, one-deep:
carbsgears <- split(mtcars, mtcars[,c("carb", "gear")], drop = TRUE)
ggs <- lapply(carbsgears, function(dat) {
ggplot(dat, aes(x = wt, y = mpg, color = disp)) + geom_point()
})
Here, ggs is a list only one-deep. The names are just concatenated strings of the two fields, so since we have mtcars$carb with values c(1,2,3,4,6,8) and mtcars$gear with values c(3,4,5), removing combinations without data we have names:
names(ggs)
# [1] "1.3" "2.3" "3.3" "4.3" "1.4" "2.4" "4.4" "2.5" "4.5" "6.5" "8.5"
where "1.3" is carb == 1 and gear == 3. When column names have dots in them, this might become ambiguous.
ggplot(mtcars, aes(x = wt, y = mpg, color = disp)) + facet_grid(vs ~ carb) + geom_point() (where you might instead choose facet_grid(ID ~ ID2)).
lapply. That would handle OP's use case above. The choice between many separate plots and a single faceted plot is multi-dimensional. There is no absolute answer. The better option will change on a case-by-case basis and will depend on the data, the message you want to convey, the audience ... and personal preference.split option.
applyfamily of functions (which force evaluation) rather than aforloop, which does not. More detail here. Also,paste0("p_carb_",i)creates a character string, which is not valid as the target of an assignment.paste0("p_carb_",i)a usable target to store the plots?lapply. Moreover, the ggplot function on the left hand side contains noiterms, so all iterations will return the same result.