A dumbbell chart (also called a connected dot plot or Cleveland dot plot) compares two values for each category by displaying two dots connected by a line. It effectively visualizes differences, changes, or ranges between two data points such as before/after comparisons, gaps, or min/max values. The connected dots make it easy to see both the magnitude and direction of change.
#' anyplot.ai
#' dumbbell-basic: Basic Dumbbell Chart
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 90/100 | Created: 2026-06-30
library(ggplot2)
library(ragg)
set.seed(42)
# Theme tokens
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
GRID_COLOR <- adjustcolor(INK, alpha.f = 0.12)
# Imprint palette (hybrid-v3 sort order)
IMPRINT_PALETTE <- c(
"#009E73", # 1 — brand green → Before score
"#C475FD", # 2 — lavender → After score
"#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477", "#99B314"
)
# Data: department wellness scores before and after a workplace initiative
departments <- c("Engineering", "Marketing", "Finance", "Operations",
"Research", "Sales", "HR", "Product", "Design", "Support")
before <- c(62, 71, 58, 74, 68, 79, 65, 72, 67, 75)
after <- c(78, 83, 71, 81, 84, 88, 76, 85, 79, 82)
df <- data.frame(
department = departments,
before = before,
after = after,
diff = after - before
)
# Sort by improvement so largest gains appear at the top
df <- df[order(df$diff), ]
df$department <- factor(df$department, levels = df$department)
# Plot
p <- ggplot(df) +
geom_segment(
aes(x = before, xend = after, y = department, yend = department),
color = INK_SOFT,
linewidth = 0.7,
alpha = 0.5
) +
geom_point(
aes(x = before, y = department, color = "Before"),
size = 3.5
) +
geom_point(
aes(x = after, y = department, color = "After"),
size = 3.5
) +
scale_color_manual(
values = c("Before" = IMPRINT_PALETTE[1], "After" = IMPRINT_PALETTE[2]),
breaks = c("Before", "After"),
name = NULL
) +
scale_x_continuous(
expand = expansion(mult = 0.05)
) +
labs(
x = "Wellness Score",
y = NULL,
title = "dumbbell-basic · r · ggplot2 · anyplot.ai"
) +
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_line(color = GRID_COLOR, linewidth = 0.4),
panel.grid.major.y = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
axis.line.x = element_line(color = INK_SOFT, linewidth = 0.5),
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,
margin = margin(b = 16)),
plot.margin = margin(t = 20, r = 24, b = 16, l = 16),
legend.position = "top",
legend.justification = "left",
legend.background = element_rect(fill = ELEVATED_BG, color = NA),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.key = element_rect(fill = NA, color = NA),
legend.margin = margin(b = 4)
) +
guides(color = guide_legend(override.aes = list(size = 4)))
# 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 Basic Dumbbell Chart on anyplot.ai.