36  Grouped scatter plots

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


This graph requires:

✅ two numeric (continuous) variable

✅ a categorical variable

36.1 Description

Grouped scatter-plots display the relationships between two continuous variables across a third categorical variable.

The x and y position displays the relationship between the two continuous variables, and color is used to distinguish between the categorical levels.

36.2 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…

36.3 Grammar

CODE:

  • Create labels with labs()

  • Initialize the graph with ggplot() and provide data

  • Map bill_length_mm to the x axis

  • Map flipper_length_mm to the y axis

  • Map species to color inside the geom_point()

show/hide 
labs_grp_scatter <- labs(
  title = "Bill Length vs. Flipper Length",
  x = "Bill Length (mm)", 
  y = "Flipper length (mm)", 
  color = "Species")

ggp2_grp_scatter <- penguins |> 
  ggplot(
    aes(x = bill_length_mm, 
        y = flipper_length_mm)) + 
  geom_point(aes(color = species)) 

ggp2_grp_scatter + 
  labs_grp_scatter

GRAPH:

Adjust over-plotting with transparency (alpha).