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.
Plot Examples
For these visualizations, we will use the penguins
dataset from the palmerpenguins package.
Scatter Plot
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()
Histogram
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`.
Box Plot
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 values (`stat_boxplot()`).
Density Plot
p <- ggplot(penguins, aes(bill_depth_mm)) +
geom_density() +
labs(
title = "Density of Penguin Bill Depth",
x = "Bill Depth (mm)",
y = "Densiy"
)
p +
theme_duke()
Jitter Plot
p <- ggplot(penguins, aes(year, body_mass_g)) +
geom_jitter() +
labs(
title = "Comparison of Body Mass By Year",
x = "Year",
y = "Body Mass (g)"
)
p +
theme_duke()