A split violin plot displaying two distributions side-by-side within each violin, with each half representing a different group. Unlike standard violin plots that mirror the same distribution, split violins use the left and right halves to compare two conditions (such as before/after, male/female, or control/treatment) at each category level. This enables direct visual comparison of distribution shapes between paired groups.
# anyplot.ai
# violin-split: Split Violin Plot
# Library: makie 0.21.9 | Julia 1.11.9
# Quality: 95/100 | Created: 2026-09-09
using CairoMakie
using Colors
using Random
using Statistics
Random.seed!(42)
# --- Theme tokens -----------------------------------------------------------
THEME = get(ENV, "ANYPLOT_THEME", "light")
PAGE_BG = THEME == "light" ? colorant"#FAF8F1" : colorant"#1A1A17"
INK = THEME == "light" ? colorant"#1A1A17" : colorant"#F0EFE8"
INK_SOFT = THEME == "light" ? colorant"#4A4A44" : colorant"#B8B7B0"
# Imprint categorical palette — theme-independent, first series always brand green
IMPRINT_PALETTE = [
colorant"#009E73", colorant"#C475FD", colorant"#4467A3", colorant"#BD8233",
colorant"#AE3030", colorant"#2ABCCD", colorant"#954477", colorant"#99B314",
]
# --- Data ---------------------------------------------------------------
# Crop yields under two irrigation regimes, compared across four crop types.
crops = ["Wheat", "Corn", "Soybean", "Rice"]
n_per_group = 220
irrigated_mean = [4.3, 6.1, 3.2, 6.6]
irrigated_std = [0.55, 0.75, 0.45, 0.85]
rainfed_mean = [2.7, 4.0, 2.2, 3.9]
rainfed_std = [0.70, 0.90, 0.55, 1.00]
x_irrigated = Int[]
y_irrigated = Float64[]
x_rainfed = Int[]
y_rainfed = Float64[]
for i in 1:length(crops)
append!(x_irrigated, fill(i, n_per_group))
append!(y_irrigated, irrigated_mean[i] .+ irrigated_std[i] .* randn(n_per_group))
append!(x_rainfed, fill(i, n_per_group))
if crops[i] == "Rice"
# Rain-fed rice is drought-sensitive: yield clusters into a low mode in
# dry years and a high mode in favorable-rainfall years, unlike the
# single-mode variability of the other crop/regime combinations.
n_drought = round(Int, 0.35 * n_per_group)
n_favorable = n_per_group - n_drought
append!(
y_rainfed,
vcat(
2.3 .+ 0.35 .* randn(n_drought),
4.6 .+ 0.55 .* randn(n_favorable),
),
)
else
append!(y_rainfed, rainfed_mean[i] .+ rainfed_std[i] .* randn(n_per_group))
end
end
# Median yield per crop/regime drives the callout below (computed from the
# generated samples so it matches whatever the violins actually show).
irrigated_medians = [median(y_irrigated[x_irrigated .== i]) for i in 1:length(crops)]
rainfed_medians = [median(y_rainfed[x_rainfed .== i]) for i in 1:length(crops)]
gains = irrigated_medians .- rainfed_medians
gain_idx = argmax(gains)
# --- Plot -----------------------------------------------------------------
fig = Figure(
resolution = (1600, 900),
fontsize = 14,
backgroundcolor = PAGE_BG,
)
ax = Axis(
fig[1, 1];
title = "violin-split · julia · makie · anyplot.ai",
titlesize = 28,
titlecolor = INK,
xlabel = "Crop",
ylabel = "Yield (tons per hectare)",
xlabelsize = 16,
ylabelsize = 16,
xlabelcolor = INK,
ylabelcolor = INK,
xticklabelsize = 14,
yticklabelsize = 14,
xticklabelcolor = INK_SOFT,
yticklabelcolor = INK_SOFT,
xtickcolor = INK_SOFT,
ytickcolor = INK_SOFT,
backgroundcolor = PAGE_BG,
topspinevisible = false,
rightspinevisible = false,
leftspinecolor = INK_SOFT,
bottomspinecolor = INK_SOFT,
xgridvisible = false,
ygridcolor = RGBAf(INK.r, INK.g, INK.b, 0.15),
xticks = (1:length(crops), crops),
)
violin!(
ax, x_irrigated, y_irrigated;
side = :left,
color = (IMPRINT_PALETTE[1], 0.85),
strokewidth = 1.5,
strokecolor = IMPRINT_PALETTE[1],
width = 0.85,
show_median = true,
mediancolor = INK,
datalimits = (0, Inf), # yield cannot be negative; trim the KDE tail at zero
)
violin!(
ax, x_rainfed, y_rainfed;
side = :right,
color = (IMPRINT_PALETTE[2], 0.85),
strokewidth = 1.5,
strokecolor = IMPRINT_PALETTE[2],
width = 0.85,
show_median = true,
mediancolor = INK,
datalimits = (0, Inf), # yield cannot be negative; trim the KDE tail at zero
)
# Storytelling callout: bracket the crop with the largest irrigated-vs-rain-fed
# median gain, offset (in screen space, toward whichever neighboring gap has
# room) so it reads next to the violins without clipping against the axis edge.
callout_side = gain_idx <= length(crops) / 2 ? 1 : -1
bracket!(
ax,
gain_idx, irrigated_medians[gain_idx],
gain_idx, rainfed_medians[gain_idx];
text = "Largest irrigation gain: +$(round(gains[gain_idx], digits = 1)) t/ha ($(crops[gain_idx]))",
offset = callout_side * 70,
width = 12,
orientation = :up,
style = :square,
color = INK_SOFT,
textcolor = INK,
fontsize = 13,
rotation = 0,
align = (callout_side > 0 ? :left : :right, :center),
)
legend_elements = [
PolyElement(color = (IMPRINT_PALETTE[1], 0.85), strokecolor = IMPRINT_PALETTE[1], strokewidth = 1.5),
PolyElement(color = (IMPRINT_PALETTE[2], 0.85), strokecolor = IMPRINT_PALETTE[2], strokewidth = 1.5),
]
Legend(
fig[1, 1], legend_elements, ["Irrigated", "Rain-fed"];
tellwidth = false, tellheight = false,
halign = :left, valign = :top,
framevisible = false, labelcolor = INK, labelsize = 14,
margin = (20, 20, 20, 20),
)
# --- Save -----------------------------------------------------------------
save("plot-$(THEME).png", fig; px_per_unit = 2)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/violin-split/makie/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "violin-split",
"language": "julia",
"library": "makie",
"page": "https://anyplot.ai/violin-split/julia/makie",
"hub": "https://anyplot.ai/violin-split",
"code_json": "https://api.anyplot.ai/specs/violin-split/makie/code",
"spec_json": "https://api.anyplot.ai/specs/violin-split",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/violin-split/julia/makie/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/violin-split/julia/makie/plot-dark.png",
"quality_score": 95.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Split Violin Plot on anyplot.ai.