This vignette is intended to
demonstrate the breadth of theme_duke()
and its various
applications. Similar to the other functions within the
theme()
, this function can be applied to all visualizations
made with ggplot2.
For these visualizations, we will use the penguins
dataset from the palmerpenguins package.
p <- ggplot(penguins, aes(bill_length_mm, flipper_length_mm)) +
geom_point(aes(colour = species)) +
labs(
title = "Bill Length vs. Flipper Length",
caption = "There are three different species of penguins.",
x = "Bill Length (mm)",
y = "Flipper Length (mm)"
)
p +
theme_duke()
p <- ggplot(penguins, aes(species)) +
geom_bar(aes(fill = species)) +
labs(
title = "Species Count",
caption = "There are three different species of penguins.",
x = "Species",
y = "Count"
)
p +
theme_duke()
p <- ggplot(penguins, aes(body_mass_g)) +
geom_histogram(aes(fill = species)) +
labs(
title = "Distribution of Penguin Body Mass",
caption = "There are three different species of penguins.",
x = "Body Mass (g)",
y = "Count"
)
p +
theme_duke()
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p <- ggplot(penguins, aes(sex, body_mass_g)) +
geom_boxplot() +
labs(
title = "Comparison of Body Mass By Sex",
x = "Sex",
y = "Body Mass (g)"
)
p +
theme_duke()
#> Warning: Removed 2 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).