39  Parallel sets

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


This graph requires:

✅ three categorical variables

✅ a numeric variable of counts

39.1 Description

Parallel sets (also referred to as Sankey diagrams or Alluvial charts) show the counts of categorical variables connected via a two-sided parallel display (or ‘sets’). Parallel sets can also be used to show different states of paired dependent relationships (such as input vs output), or time 1 vs time 2.

The height of the connecting bands between the categories on the x axis represent the relative counts for each discrete level (displayed on the y axis). The levels within each variable are represented with color.

We can build parallel set diagrams with the ggforce package.

Also check out alluvial charts.

39.2 Set up

PACKAGES:

Install packages.

show/hide 
# pak::pak("thomasp85/ggforce")
install.packages("palmerpenguins")
library(ggforce)
library(palmerpenguins)
library(ggplot2)

DATA:

Artwork by allison horst

We’re going to remove the missing values from palmerpenguins::penguins, count the categorical variables (island, sex, species), and rename the n column (produced by the count() function) to value.

  • ggforce has a special gather_set_data() function that changes tidy data into a tidy(er) format
show/hide 
peng_wide <- palmerpenguins::penguins |> 
  drop_na() |> 
  count(island, species, sex) |> 
  rename(value = n)
para_set_peng <- ggforce::gather_set_data(
                            data = peng_wide, 
                            x = 1:3)
dplyr::glimpse(para_set_peng)
#> Rows: 30
#> Columns: 7
#> $ island  <fct> Biscoe, Biscoe, Biscoe, Biscoe, …
#> $ species <fct> Adelie, Adelie, Gentoo, Gentoo, …
#> $ sex     <fct> female, male, female, male, fema…
#> $ value   <int> 22, 22, 58, 61, 27, 28, 34, 34, …
#> $ id      <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1…
#> $ x       <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2,…
#> $ y       <fct> Biscoe, Biscoe, Biscoe, Biscoe, …

39.3 Grammar

CODE:

  • Create labels with labs()

  • Initialize the graph with ggplot() and provide data

  • Map x to x, id to id, y to split, and value to value

  • In the geom_parallel_sets() function, map sex to fill and manually set the alpha (opacity) and the axis.width

  • In the geom_parallel_sets_axes() function, set the axis.width to the same value as the geom_parallel_sets() above

  • For labeling, adjust the size manually and set the color to something that stands out against the black vertical axes

  • Manually label the x axis with scale_x_continuous(), setting the breaks and labels to the variable names in the peng_wide dataset

  • Finally, remove the x title with axis.title.x = element_blank()

show/hide 
labs_psets <- labs(
        title = "Categories of Palmer Penguins", 
        y = "Count", fill = "Sex")

ggp2_psets <- ggplot(data = para_set_peng, 
    mapping = aes(x = x, 
        id = id, 
        split = y, 
        value = value)) +
  geom_parallel_sets(aes(fill = sex), 
        alpha = 0.3, 
        axis.width = 0.07) 

ggp2_psets_axes <- ggp2_psets +
  geom_parallel_sets_axes(
        axis.width = 0.07) 

ggp2_psets_labs <- ggp2_psets_axes +
  geom_parallel_sets_labels(
        size = 2.0, 
        color = '#ffffff') +
  scale_x_continuous(
        breaks = c(1, 2, 3), 
        labels = c("Island", "Species", "Sex")) +
  theme(axis.title.x = element_blank())

ggp2_psets_labs +
    labs_psets

GRAPH:

39.4 More info

If the categories have long names, you can move the location of the labels outside the set.

39.4.1 Labeling sets

If the categories have long names, use the angle, nudge_x/nudge_y and hjust/vjust in geom_parallel_sets_labels() to adjust the size, location, and color of the labels.

  • Manually setting the limits of the x axis in scale_x_continuous() will also give more room for the labels.
show/hide 
ggp2_psets_axes + 
  geom_parallel_sets_labels(
      size = 3.2, 
      colour = '#000000',
      angle = 0, 
      nudge_x = 0.1, 
      hjust = 0) + 
  scale_x_continuous(
        limits = c(0.9, 3.2),
        breaks = c(1, 2, 3), 
        labels = c("Island", "Species", "Sex")) + 
  theme(axis.title.x = element_blank()) + 
    labs_psets