Getting Started with ggfunction • ggfunction

Installation

# Install from GitHub
pak::pak("dusty-turner/ggfunction")

Your first plot

Pass any $\mathbb{R} \to \mathbb{R}$ function and a domain:

ggplot() +
  geom_function_1d_1d(fun = sin, xlim = c(0, 2 * pi))

Shading a region

Use shade_from and shade_to to highlight an interval under the curve:

ggplot() +
  geom_function_1d_1d(
    fun = dnorm, xlim = c(-3, 3),
    shade_from = -1, shade_to = 1, fill = "steelblue"
  )

Plotting a distribution

geom_pdf() is purpose-built for density functions. Use p to shade a cumulative probability region:

ggplot() +
  geom_pdf(fun = dnorm, xlim = c(-3, 3), p = 0.975, fill = "tomato")

Discrete distributions

geom_pmf() renders probability mass functions as lollipop charts:

ggplot() +
  geom_pmf(
    fun = dbinom, xlim = c(0, 10),
    args = list(size = 10, prob = 0.3)
  )

Working with data

geom_ecdf() builds an empirical CDF from observed data, with an automatic Kolmogorov–Smirnov confidence band:

set.seed(42)
df <- data.frame(x = rnorm(50))

ggplot(df, aes(x = x)) +
  geom_ecdf()

Layering with ggplot2

Every ggfunction geom is a standard ggplot2 layer. Add themes, titles, and other geoms as usual:

ggplot() +
  geom_pdf(fun = dnorm, xlim = c(-3, 3),
           p_lower = 0.025, p_upper = 0.975,
           fill = "steelblue") +
  labs(
    title = "Standard Normal Distribution",
    subtitle = "Central 95% shaded",
    x = "x", y = "Density"
  ) +
  theme_minimal()