2026-07-02
ggfun collects small but useful extensions for ggplot2. The package focuses on tools that make it easier to style plots, add custom geometric layers, work with legends, and inspect or modify existing plot objects.
This vignette groups the functions by the type of task they solve.
element_roundrect() works like element_rect(), but draws rounded rectangle backgrounds. It can be used in theme elements such as facet strips, legends, panel backgrounds, and plot backgrounds.
p <- ggplot(mpg, aes(displ, cty)) +
geom_point(alpha = 0.7) +
facet_grid(cols = vars(cyl))
p + theme(
strip.background = element_roundrect(
fill = "grey35",
color = NA,
r = 0.15
),
strip.text = element_text(color = "white")
)
ggplot(mtcars, aes(mpg, disp, color = factor(cyl), size = wt)) +
geom_point(alpha = 0.8) +
theme(
legend.background = element_roundrect(
fill = "grey97",
color = "grey55",
linetype = 2,
r = 0.08
)
)
element_blinds() and theme_blinds() draw alternating bands on major grid lines. This is useful when categorical axes need more visual separation.
df_blinds <- data.frame(
group = rep(LETTERS[1:6], each = 3),
sample = rep(c("A", "B", "C"), 6),
value = c(2, 4, 3, 5, 3, 4, 4, 6, 5, 6, 5, 7, 3, 4, 6, 5, 7, 6)
)
ggplot(df_blinds, aes(sample, group)) +
geom_point(aes(size = value, color = value)) +
scale_color_viridis_c() +
theme_blinds(axis = "y", colour = c("grey95", "white")) +
theme(panel.grid.major.x = element_blank())
Several small theme helpers remove common plot decorations.
ggplot(mtcars, aes(mpg, disp)) +
geom_point(aes(color = factor(cyl)), size = 2) +
theme_noxaxis()
ggplot(mtcars, aes(mpg, disp)) +
geom_point(aes(color = factor(cyl)), size = 2) +
theme_transparent()
hist()geom_hist() uses hist() to compute break midpoints and counts. This makes it useful when the goal is to reproduce base R histogram calculations inside a ggplot2 layer.
set.seed(42)
df_hist <- data.frame(
value = c(rnorm(120), rnorm(120, mean = 2)),
group = rep(c("A", "B"), each = 120)
)
ggplot(df_hist, aes(value, fill = group)) +
geom_hist(breaks = 16, position = "identity", alpha = 0.55, color = "white")
geom_xspline() draws an X-spline through control points. Positive shape values produce smoother curves, while negative values pull the curve toward the control points.
set.seed(123)
df_line <- data.frame(
x = rep(1:10, 2),
y = c(cumsum(rnorm(10)), cumsum(rnorm(10, sd = 0.7)) + 2),
series = rep(c("A", "B"), each = 10)
)
ggplot(df_line, aes(x, y, color = series, group = series)) +
geom_point(size = 2) +
geom_xspline(linewidth = 1, shape = 1)
geom_segment_c() draws line segments whose colors transition from col0 to col1.
df_segments <- data.frame(
x = c(0, 1, 2, 3),
xend = c(1, 2, 3, 3),
y = c(0, 1, 0.5, 0),
yend = c(1, 0.5, 1.5, 1.5),
start = c(0.1, 0.3, 0.5, 0.7),
end = c(0.4, 0.6, 0.9, 1.0)
)
ggplot(df_segments) +
geom_segment_c(
aes(x = x, y = y, xend = xend, yend = yend, col0 = start, col1 = end),
linewidth = 2,
lineend = "round"
) +
scale_color_viridis_c(name = "value") +
coord_equal()
geom_scatter_rect(), geom_triangle(), and geom_cake() are convenient when a plot needs custom glyph-like markers.
df_rect <- data.frame(
x = rep(1:5, 2),
y = rep(1:2, each = 5),
value = c(1, 3, 2, 4, 5, 2, 4, 3, 5, 6)
)
ggplot(df_rect, aes(x, y)) +
geom_scatter_rect(aes(fill = value), width = 0.85, height = 0.5, color = "white") +
scale_y_continuous(breaks = 1:2, labels = c("control", "treated")) +
scale_fill_viridis_c()
df_glyph <- data.frame(
x = 1:4,
y = c(1, 2, 1.4, 2.4),
angle = c(0, 45, 90, 135),
cake_size = c(0.18, 0.2, 0.16, 0.22)
)
ggplot(df_glyph, aes(x, y)) +
geom_triangle(aes(angle = angle), fill = "tomato", size = 16, alpha = 0.8) +
geom_cake(aes(y = y + 0.45, size = cake_size), colour.cake = "pink") +
coord_equal(xlim = c(0.5, 4.5), ylim = c(0.5, 3.2)) +
theme_noaxis()
facet_set() can relabel existing facets or add a simple facet strip to a plot.
p_facet <- ggplot(mtcars, aes(disp, drat)) +
geom_point() +
facet_grid(cols = vars(am), rows = vars(cyl))
p_facet + facet_set(label = c(`0` = "Automatic", `1` = "Manual", `6` = "Six cylinders"))
ggplot(mtcars, aes(mpg, disp)) +
geom_point() +
facet_set("Motor Trend cars")
get_aes_var() returns the variable used by a mapping, and get_plot_data() extracts variables from the data associated with a plot or layer.
p_data <- ggplot(mtcars, aes(mpg, disp, color = factor(cyl))) +
geom_point()
get_aes_var(p_data$mapping, "x")
#> [1] "mpg"
head(get_plot_data(p_data, var = c("x", "y")))
#> mpg disp
#> Mazda RX4 21.0 160
#> Mazda RX4 Wag 21.0 160
#> Datsun 710 22.8 108
#> Hornet 4 Drive 21.4 258
#> Hornet Sportabout 18.7 360
#> Valiant 18.1 225xrange(), yrange(), and ggrange() summarize the visible data range of a plot.
xrange(p_data)
#> [1] 9.225 35.075
yrange(p_data)
#> [1] 51.055 492.045
ggrange(p_data, var = "x", region = "plot", type = "range")
#> [1] 10.4 33.9get_legend() extracts the legend grob from a plot.
p_legend <- ggplot(mtcars, aes(mpg, disp, color = factor(cyl))) +
geom_point(size = 2)
legend <- get_legend(p_legend)
class(legend)
#> [1] "gtable" "gTree" "grob" "gDesc"gglegend() adds a manual legend by drawing an invisible helper layer.
p_base <- ggplot(mtcars, aes(mpg, disp)) +
geom_point()
legend_data <- data.frame(
colour = c("firebrick", "steelblue"),
label = c("Group A", "Group B")
)
gglegend(aes(colour = label, label = label), legend_data, geom_text, p_base)
set_font() edits text grobs after a plot has been converted to a gtable. It draws the result and returns the edited grob invisibly.
df_text <- data.frame(
x = 1:5,
y = c(2, 3, 2.5, 4, 3.5),
label = LETTERS[1:5]
)
p_text <- ggplot(df_text, aes(x, y, label = label)) +
geom_text(size = 5) +
labs(title = "Edited text grobs")
set_font(p_text, family = "serif", fontface = "italic", color = "firebrick")
The functions in ggfun are intentionally small and composable. They are most useful when a plot is almost complete but needs a custom theme element, a specialized layer, a modified facet strip, or access to the data and grobs that ggplot2 builds internally.