The Grammar of Graphics

Meet the Palmer Penguins 

library(palmerpenguins)
penguins
# A tibble: 344 × 8
   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
   <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
 1 Adelie  Torgersen           39.1          18.7               181        3750
 2 Adelie  Torgersen           39.5          17.4               186        3800
 3 Adelie  Torgersen           40.3          18                 195        3250
 4 Adelie  Torgersen           NA            NA                  NA          NA
 5 Adelie  Torgersen           36.7          19.3               193        3450
 6 Adelie  Torgersen           39.3          20.6               190        3650
 7 Adelie  Torgersen           38.9          17.8               181        3625
 8 Adelie  Torgersen           39.2          19.6               195        4675
 9 Adelie  Torgersen           34.1          18.1               193        3475
10 Adelie  Torgersen           42            20.2               190        4250
# ℹ 334 more rows
# ℹ 2 more variables: sex <fct>, year <int>

Question: In terms of the way they are constructed…

What do these plots have in common? How do they differ?

01:20

Question: What do these plots have in common? How do they differ?

01:20

The Grammar of Graphics

“The Grammar of Graphics”

Leland Wilkinson (1999)

  • A grammar to describes all statistical graphics.
  • Underlies most modern data visualization software.

Aesthetic Mapping

An aesthetic mapping links a variable in the data to a visual channel that can encode its variation.

Channels for ordered variables

Aesthetic Mapping

An aesthetic mapping links a variable in the data to a visual channel that can encode its variation.

Channels for unordered variables

Geometry

The geometry describes how to translate the observations into marks on the page.

Examples

  • Point
  • Line
  • Bar

Named plots

Redux 1

Redux 1

Question: What are the aesthetic mappings and geometries used here?

01:30

ggplot2

ggplot2()

A plot can be decomposed into three primary elements:

  1. the data,
  2. the aesthetic mapping of the variables in the data to visual channels, and
  3. the geometry used to translate the observations into marks on the plot.

penguins |>
  select(bill_length_mm,
         flipper_length_mm,
         species)
# A tibble: 344 × 3
   bill_length_mm flipper_length_mm species
            <dbl>             <int> <fct>  
 1           39.1               181 Adelie 
 2           39.5               186 Adelie 
 3           40.3               195 Adelie 
 4           NA                  NA Adelie 
 5           36.7               193 Adelie 
 6           39.3               190 Adelie 
 7           38.9               181 Adelie 
 8           39.2               195 Adelie 
 9           34.1               193 Adelie 
10           42                 190 Adelie 
# ℹ 334 more rows

penguins |>
  ggplot(aes(x = bill_length_mm,
             y = flipper_length_mm,
             color = species)) +
  geom_point()

ggplot2() syntax

ggplot2() builds a plot layer by layer, each one added on top of one another with + (not |>).

  • ggplot(df) creates canvas
  • aes() creates mappings, called inside ggplot() or a geom()
  • geom_() puts down marks using declared geometry

Layer by layer

penguins |>
  ggplot(aes(x = bill_length_mm,
             y = flipper_length_mm,
             color = species)) +
  geom_point() +
  theme_gray(base_size = 18)

Common aes()

  • x
  • y
  • color
  • fill
  • size
  • shape
  • alpha

Common geom_()

  • geom_point()
  • geom_bar() / geom_col()
  • geom_line()
  • geom_histogram()
  • geom_boxplot()
  • geom_violin()
  • geom_density()

Mapping vs Setting

demo