6  Violin plots

This graph is largely complete and just needs final proof reading.

This graph requires:

✅ a numeric (continuous) variable


6.1 Description

Violin plots show data distribution and probability density. They are like box plots but have a rotated kernel density plot on each side. We can use them to compare data distribution across categories.

The violin plot is essentially a mirrored density plot, in which a smoothed distribution is plotted symmetrically across the x or y axis, creating a Rorschach-like inkblot area for the distribution:

source: Rorschach test, Wikipedia

6.2 Set up

PACKAGES:

Install packages.

show/hide 
install.packages("palmerpenguins")
library(palmerpenguins)
library(ggplot2)

DATA:

Artwork by Allison Horst

The penguins data.

show/hide 
penguins <- palmerpenguins::penguins
glimpse(penguins)
#> Rows: 344
#> Columns: 8
#> $ species           <fct> Adelie, Adelie, Adelie…
#> $ island            <fct> Torgersen, Torgersen, …
#> $ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, …
#> $ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, …
#> $ flipper_length_mm <int> 181, 186, 195, NA, 193…
#> $ body_mass_g       <int> 3750, 3800, 3250, NA, …
#> $ sex               <fct> male, female, female, …
#> $ year              <int> 2007, 2007, 2007, 2007…

6.3 Grammar

CODE:

Create labels with labs()

Initialize the graph with ggplot() and provide data

  • Place an empty string ("") in the x argument

Map and empty string ("") to the x and flipper_length_mm to the y

Add geom_violin()

show/hide 
labs_violin <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "",
  y = "Flipper length (millimeters)")
ggp2_violin <- ggplot(data = penguins,
       aes(x = '', 
           y = flipper_length_mm)) +
       geom_violin() 
ggp2_violin + 
  labs_violin

GRAPH: