A grouped bar chart that displays multiple bars side-by-side for each category, enabling direct comparison of values across different groups within the same categorical dimension. This visualization excels at showing how different groups perform relative to each other across multiple categories, making patterns and differences immediately apparent. Grouped bar charts are essential for comparative analysis where you need to track multiple series against the same set of categories.
#' anyplot.ai
#' bar-grouped: Grouped Bar Chart
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 92/100 | Created: 2026-08-05
library(ggplot2)
library(dplyr)
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"
# element_line() has no `alpha` argument, so bake a ~20% opacity into the hex
# itself (0x33 = 51/255) to get the style guide's "subtle" gridline.
GRID_COLOR <- paste0(INK, "33")
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314")
# --- Data ---------------------------------------------------------------
regions <- c("North", "South", "East", "West", "Central")
products <- c("Software", "Hardware", "Services")
df <- expand.grid(region = regions, product = products) %>%
mutate(
product = factor(product, levels = products),
revenue = case_when(
product == "Software" ~ round(rnorm(n(), mean = 5.8, sd = 0.9), 1),
product == "Hardware" ~ round(rnorm(n(), mean = 4.2, sd = 1.1), 1),
TRUE ~ round(rnorm(n(), mean = 3.0, sd = 0.6), 1)
)
)
# Order regions by total revenue (descending) so the chart reads as a ranking
# rather than an arbitrary list.
region_order <- df %>%
group_by(region) %>%
summarise(total = sum(revenue), .groups = "drop") %>%
arrange(desc(total)) %>%
pull(region)
df <- df %>% mutate(region = factor(region, levels = region_order))
# --- Plot -----------------------------------------------------------------
p <- ggplot(df, aes(x = region, y = revenue, fill = product)) +
geom_col(
position = position_dodge(width = 0.75),
width = 0.68,
color = PAGE_BG,
linewidth = 0.4
) +
geom_text(
aes(label = sprintf("%.1f", revenue)),
position = position_dodge(width = 0.75),
vjust = -0.5,
size = 2.4,
color = INK_SOFT
) +
scale_fill_manual(values = IMPRINT_PALETTE[1:3], name = "Product Line") +
scale_y_continuous(expand = expansion(mult = c(0, 0.14))) +
labs(
title = "Revenue by Product Line · bar-grouped · r · ggplot2 · anyplot.ai",
x = "Region",
y = "Revenue ($M)"
) +
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.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.y = element_line(color = GRID_COLOR, linewidth = 0.25),
axis.line = element_line(color = INK_SOFT, linewidth = 0.4),
axis.ticks = element_blank(),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
plot.title = element_text(color = INK, size = 12, face = "bold"),
legend.position = "top",
legend.justification = "left",
legend.background = element_blank(),
legend.key = element_blank(),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 10),
plot.margin = margin(t = 10, r = 16, b = 8, l = 8)
)
# --- 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 Bar Chart on anyplot.ai.