8  Grouped bar graphs

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

This graph requires:

✅ a categorical variable

✅ a numeric (continuous) variable

8.1 Description

Grouped bar graphs compare multiple values across categories. Each category has a cluster of bars. X-axis labels show categories and y-axis values. Colors or patterns differentiate subsets, and a legend is shown on the side or top of the graph.

geom_col() allows us to display ‘grouped’ numerical values across levels (or groups) of a categorical variable.

8.2 Set up

PACKAGES:

Install packages.

install.packages("palmerpenguins")
library(palmerpenguins) 
library(ggplot2)

DATA:

Artwork by Allison Horst

Remove the missing values and reduce the palmerpenguins::penguins dataset to only body_mass_g and island, then group the data by island and calculate the sum of body_mass_g (as sum_body_mass_g).

peng_grp_col <- palmerpenguins::penguins |>
    dplyr::select(body_mass_g, island) |> 
    tidyr::drop_na() |> 
    dplyr::group_by(island) |>
    dplyr::summarise(
        sum_body_mass_g = sum(body_mass_g)
        ) |>
    dplyr::ungroup()
glimpse(peng_grp_col)
#> Rows: 3
#> Columns: 2
#> $ island          <fct> Biscoe, Dream, Torgersen
#> $ sum_body_mass_g <int> 787575, 460400, 189025

8.3 Grammar

CODE:

Grouped bar graphs assume the statistical measure (i.e., the value that the length of the bars will be derived from) is contained in a variable and mapped to the x or y aesthetic.

• Create labels with labs()

• Initialize the graph with ggplot() and provide data

• Map island to the x and sum_body_mass_g to the y

• Map island to fill inside the aes() of geom_col()

labs_grp_col <- labs(
    title = "Total Penguin Mass",
    subtitle = "What's the total mass of penguins per Island?",
    x = "Island",
    y = "Total penguin body mass (g)")
ggp2_grp_col <- ggplot(data = peng_grp_col,
              aes(x = island, 
                  y = sum_body_mass_g)) + 
        geom_col(aes(fill = island),
            show.legend = FALSE)
ggp2_grp_col + 
    labs_grp_col

GRAPH:

8.4 More Info

We didn’t have to calculate sum_body_mass_g (displayed on the y axis) by island because ggplot2 does this for us!

If we pass a categorical variable to the x (like island) and a continuous variable to y (like body_mass_kg), geom_col() will calculate the sum() of y by levels of x:

  penguins |> 
  dplyr::select(body_mass_g, island) |> 
  tidyr::drop_na() |>
  ggplot(aes(x = island, y = body_mass_g)) + 
        geom_col(aes(fill = island),
            show.legend = FALSE) + 
  labs_grp_col

We can see the underlying totaling of body_mass_g using dplyr’s group_by() and summarise() functions.

palmerpenguins::penguins |> 
    dplyr::select(body_mass_g, island) |> 
    tidyr::drop_na() |> 
    dplyr::group_by(island) |>
    dplyr::summarise(
        `Total Penguin Body Mass (kg)` = sum(body_mass_g)
        ) |>
    dplyr::ungroup() |> 
    dplyr::select(`Island` = island, 
        `Total Penguin Body Mass (kg)`)

Island	Total Penguin Body Mass (kg)
Biscoe	787575
Dream	460400
Torgersen	189025