‘ggplot2’ Palettes From Tintin Comic Books

A few examples using head trauma data from the comic itself.

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Motivation

Can we easily access a colour palette that is not viridis? Yes, we can! I will show you how to use the tintin package to create colorful plots.

Here are the palette options:

Install tintin

You can install the development version of tintin like so:

remotes::install_github("pachadotdev/tintin")

Examples

How many types of injury we find in Tintin comic books? Let’s use dplyr to find out:

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(tintin)

tintin_head_trauma %>%
  group_by(cause_of_injury) %>%
  count() %>%
  arrange(desc(n)) %>%
  print(n = 29)

# A tibble: 29 × 2
# Groups:   cause_of_injury [29]
   cause_of_injury             n
   <fct>                   <int>
 1 Blow from a club            8
 2 Explosion                   4
 3 Bullet injury               3
 4 Car accident                3
 5 Chloroform poisoning        3
 6 Blow from a stick           2
 7 Dehydration                 2
 8 Hit by a brick              2
 9 Hitting a tree trunk        2
10 Hypoxemia                   2
11 Avalanche                   1
12 Blow from a billy club      1
13 Falling down stairs         1
14 Falling on ice              1
15 Fight with a lion           1
16 G-force                     1
17 Gas poisoning               1
18 Hit by a board              1
19 Hit by a camel femur        1
20 Hit by a camera             1
21 Hit by a rake               1
22 Hit by a tree trunk         1
23 Hit by a whisky bottle      1
24 Punch                       1
25 Struck by a giant apple     1
26 Struck by a sword           1
27 Struck by an oar            1
28 Struck by Snowy             1
29 Train accident              1

How about we condense the data a bit? Let’s use forcats::fct_lump to group the injuries and obtain the five most common causes of injury:

library(forcats)

tintin_head_trauma %>%
  mutate(cause_of_injury = fct_lump(cause_of_injury, 5)) %>%
  filter(cause_of_injury != "Other") %>%
  group_by(cause_of_injury) %>%
  count() %>%
  arrange(desc(n))

# A tibble: 5 × 2
# Groups:   cause_of_injury [5]
  cause_of_injury          n
  <fct>                <int>
1 Blow from a club         8
2 Explosion                4
3 Bullet injury            3
4 Car accident             3
5 Chloroform poisoning     3

Now, let’s plot the number of injuries per year using ggplot2 but creating intervals for the loss of consciousness variable:

library(ggplot2)

dplot <- tintin_head_trauma %>%
  mutate(
    locs_interval = cut(
      loss_of_consciousness_severity,
      breaks = 5
    )
  ) %>%
  group_by(year, locs_interval) %>%
  count()

g <- ggplot(dplot) +
  geom_col(aes(x = as.factor(year), y = n, fill = locs_interval)) +
  theme_minimal(base_size = 13) +
  theme(axis.text.x = element_text(angle = 30)) +
  labs(x = "Year",
    y = "Number of injuries",
    fill = "Severity",
    title = "Tintin's Head Trauma")

g

Now let’s use the tintin package to add colours:

# Top 3 books by count of injuries
tintin_head_trauma %>%
  group_by(book_title) %>%
  count() %>%
  arrange(desc(n)) %>%
  print(n = 3)

# A tibble: 16 × 2
# Groups:   book_title [16]
  book_title             n
  <fct>              <int>
1 Land of Black Gold     6
2 The Black Island       5
3 Tintin in America      5
# ℹ 13 more rows

g + 
  scale_fill_tintin_d(option = "land_of_black_gold")

g + 
  scale_fill_tintin_d(option = "the_black_island")

g + 
  scale_fill_tintin_d(option = "tintin_in_america")

More examples

Check the package’s repository for more examples.