ggplot snippet to show responses as density plots

plot_four_scales.R

if (!require("pacman")) install.packages("pacman")
pacman::p_load("tidyverse",  "ggpubr", "see")

set.seed(123)
n = 100
df = data.frame(
  part = paste0("id", 1:n),
  scale_A = rnorm(n, m = 10, sd = 5),
  # does not work well in Likert type variables 
  scale_B = sample(0:5, n, replace = TRUE, prob = c(0.1, 0.15, 0.4, 0.2, 0.1, 0.05)),
  scale_C = abs(rnorm(n, m = 0, sd = 5)),
  scale_D = rnorm(n, m = 10, sd = 5)
)
# The data-frame must be in long format
# the code assumes that columns are adjacent
df_long <- df %>% pivot_longer(cols =  scale_A:scale_D) %>% 
# Change the names to a more intruitive ones 
  mutate(name = case_when(
    name == "scale_A" ~ "A",
    name == "scale_B" ~ "B",
    name == "scale_C" ~ "C",
    name == "scale_D" ~ "D"
  )) 

# we specify what we want to plot in aes
df_long %>% ggplot(aes(x = value, fill = name)) +
  # alternative is to use geom_histogram
  geom_density() +
  # here we specify that each scale response must be in one facet
    facet_wrap( ~ name, 
                ncol = 1, # change the numbner of columns to play with disposition 
                scales = "free") + # remove scales = "free" if everything is in te same sclae
  theme_modern() + 
  # if you prefer without color use the following
  # scale_fill_manual(values = c("darkgrey","darkgreyk", "darkgrey", "darkgrey")) + 
  scale_fill_manual(values = c("#58d68d","#804a87", "#fc03c2", "#0356fc")) + 
  # labs
  xlab("") +
  ylab("Desnsity") +
  # remove legend as each facet provides the title
  theme(legend.position = "none", legend.title = element_blank()) +
  ggtitle("Title of the figure")

# saving the plot, you can change size,  units and name. By default 
# it takes the last plot executed
ggsave("fig.png", width = 10, height = 10, units = "in")