A grouped box plot displays multiple box plots side-by-side within each category, enabling comparison of distributions across subgroups. Each group contains boxes representing different subcategories or conditions, making it ideal for multi-factor comparisons and A/B testing scenarios with multiple metrics.
#' anyplot.ai
#' box-grouped: Grouped Box Plot
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 89/100 | Created: 2026-08-18
library(ggplot2)
library(dplyr)
library(tidyr)
library(ragg)
set.seed(42)
# --- Theme tokens -------------------------------------------------------
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314")
# --- Data -----------------------------------------------------------------
departments <- c("Engineering", "Sales", "Marketing", "Support")
levels_exp <- c("Junior", "Mid", "Senior")
dept_baseline <- c(Engineering = 62, Sales = 58, Marketing = 55, Support = 60)
level_shift <- c(Junior = -8, Mid = 0, Senior = 9)
level_spread <- c(Junior = 9, Mid = 8, Senior = 7)
n_per_group <- 70
df <- expand.grid(
department = departments,
experience = levels_exp,
stringsAsFactors = FALSE
) %>%
mutate(
mean_score = dept_baseline[department] + level_shift[experience],
sd_score = level_spread[experience]
) %>%
rowwise() %>%
mutate(score = list(rnorm(n_per_group, mean = mean_score, sd = sd_score))) %>%
ungroup() %>%
unnest(score) %>%
transmute(
department = factor(department, levels = departments),
experience = factor(experience, levels = levels_exp),
score
)
# --- Plot -------------------------------------------------------------------
p <- ggplot(df, aes(x = department, y = score, fill = experience)) +
geom_boxplot(
position = position_dodge(width = 0.75),
width = 0.65,
linewidth = 0.5,
color = INK_SOFT,
outlier.size = 1.8,
outlier.alpha = 0.7
) +
stat_summary(
mapping = aes(x = department, y = score, group = experience, shape = "Mean"),
fun = mean,
geom = "point",
position = position_dodge(width = 0.75),
size = 2.2,
stroke = 0.6,
color = INK,
fill = PAGE_BG,
inherit.aes = FALSE
) +
scale_fill_manual(values = IMPRINT_PALETTE[1:3], name = "Experience Level") +
scale_shape_manual(values = c("Mean" = 23), name = NULL) +
labs(
title = "box-grouped · r · ggplot2 · anyplot.ai",
x = "Department",
y = "Productivity Score"
) +
guides(
fill = guide_legend(order = 1),
shape = guide_legend(order = 2)
) +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(color = INK_SOFT, linewidth = 0.15),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
axis.ticks = element_blank(),
plot.title = element_text(color = INK, size = 12, face = "bold"),
legend.position = "top",
legend.justification = "right",
legend.background = element_rect(fill = PAGE_BG, color = NA),
legend.key = element_rect(fill = PAGE_BG, color = NA),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 9)
)
# --- Save -------------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Part of Grouped Box Plot on anyplot.ai.