How to draw several plots with different categorical variables?

[duttashi]

This question was originally asked on SO.

I would like to find a way to quickly make these several plots. Right now, the only way I know how to do this is to create each plot individually, and then use grid_arrange to put them together. However, my real dataset has something like several categorical variables, so this would be very time intensive!

Is there a quicker and easier way to do this? I believe that the hardest part about this is that each plot has its own legend, so I'm not sure how to get around that stumbling block.

[duttashi]

Solution: Separate the categorical and continuous variables and then pass them into a custom-wrapper function.

library(tidyverse)
library(nycflights13)

cat_vars <- flights[, sapply(flights, is.character)]
cont_vars<- flights[, !sapply(flights, is.character)]
dat <- flights %>%
  select(carrier, origin, distance) %>%
  mutate(origin = origin %>% as.factor,
         carrier = carrier %>% as.factor)

func_plot_cat <- function(cat_vars) {
  dat %>%
    ggplot(aes(x = distance, fill = !!cat_vars)) +
    geom_density()
}

func_plot_cont <- function(cont_vars) {
  dat %>%
    ggplot(aes(x = distance, fill = !!cont_vars)) +
    geom_point()
}

plotlist_cat_vars <- lapply(cat_vars, func_plot_cat)
plotlist_cont_vars<- lapply(cont_vars, func_plot_cont)
print(plotlist_cat_vars)
print(plotlist_cont_vars)