Apply a ggplot-function per group with dplyr and set title per group

Question

I would like to create one separate plot per group in a data frame and include the group in the title.

With the iris dataset I can in base R and ggplot do this

plots1 <- lapply(split(iris, iris$Species), 
  function(x) 
    ggplot(x, aes(x=Petal.Width, y=Petal.Length)) +
      geom_point() +
      ggtitle(x$Species[1]))

Is there an equivalent using dplyr?

Here's an attempt using facets instead of title.

p <- ggplot(data=iris, aes(x=Petal.Width, y=Petal.Length)) + geom_point()
plots2 = iris %>% group_by(Species) %>% do(plots = p %+% . + facet_wrap(~Species))

where I use %+% to replace the dataset in p with the subset for each call.

or (working but complex) with ggtitle

plots3 = iris %>%
  group_by(Species) %>%
  do(
    plots = ggplot(data=.) +
      geom_point(aes(x=Petal.Width, y=Petal.Length)) +
      ggtitle(. %>% select(Species) %>% mutate(Species=as.character(Species)) %>% head(1) %>% as.character()))

The problem is that I can't seem to set the title per group with ggtitle in a very simple way.

Thanks!

Answer 1

Use .$Species to pull the species data into ggtitle:

iris %>% group_by(Species) %>% do(plots=ggplot(data=.) +
         aes(x=Petal.Width, y=Petal.Length) + geom_point() + ggtitle(unique(.$Species)))

Answer 2

library(dplyr, warn.conflicts = FALSE)
library(ggplot2)

plots3 <- iris %>%
  group_by(Species) %>%
  group_map(~ ggplot(.) + aes(x=Petal.Width, y=Petal.Length) + geom_point() + ggtitle(.y[[1]]))

length(plots3)
#> [1] 3
# for example, the second plot :
plots3[[2]]

^{Created on 2021-11-19 by the reprex package (v2.0.1)}

Answer 3

This is another option using rowwise:

plots2 = iris %>% 
    group_by(Species) %>% 
    do(plots = p %+% .) %>% 
    rowwise() %>%
    do(x=.$plots + ggtitle(.$Species))