A dot matrix chart displays proportions using a grid of equally-sized dots where filled or colored dots represent counts out of a total. Each dot corresponds to one unit, making it intuitive to read "X out of N" statistics at a glance. Unlike waffle charts that use percentage-based squares, dot matrix charts emphasize absolute counts with variable grid sizes, excelling at risk communication and survey result visualization.
# anyplot.ai
# dot-matrix-proportional: Dot Matrix Chart for Proportional Counts
# Library: makie 0.21.9 | Julia 1.11.9
# Quality: 93/100 | Created: 2026-09-05
using CairoMakie
using Colors
using Random
Random.seed!(42)
# --- Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome") ---
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"
# Semantic anchors (see prompts/default-style-guide.md "Semantic anchors"):
# sentiment/polarity categories map to green (positive) / red (negative) /
# adaptive muted gray (neutral) rather than the canonical palette order.
MUTED = THEME == "light" ? colorant"#6B6A63" : colorant"#A8A79F"
CATEGORY_COLOR = Dict(
"Satisfied" => colorant"#009E73",
"Neutral" => MUTED,
"Dissatisfied" => colorant"#AE3030",
)
# --- Data: customer satisfaction survey, 300 respondents -----------------------
categories = ["Satisfied", "Neutral", "Dissatisfied"]
counts = [168, 72, 60]
total = sum(counts)
n_cols = 15
n_rows = cld(total, n_cols)
dot_category = String[]
for (cat, n) in zip(categories, counts)
append!(dot_category, fill(cat, n))
end
dot_x = Float64[]
dot_y = Float64[]
for i in 0:(total - 1)
row = i ÷ n_cols
col = i % n_cols
push!(dot_x, col)
push!(dot_y, n_rows - 1 - row) # row 0 (first filled) sits at the top
end
# --- Plot -----------------------------------------------------------------------
fig = Figure(
resolution = (1200, 1200),
fontsize = 14,
backgroundcolor = PAGE_BG,
)
ax = Axis(
fig[1, 1];
title = "dot-matrix-proportional · julia · makie · anyplot.ai",
titlesize = 30,
titlecolor = INK,
subtitle = "$(total) survey respondents, one dot per person",
subtitlesize = 16,
subtitlecolor = INK_SOFT,
backgroundcolor = PAGE_BG,
aspect = DataAspect(),
)
hidedecorations!(ax)
hidespines!(ax)
for (i, cat) in enumerate(categories)
mask = dot_category .== cat
pct = round(100 * counts[i] / total; digits = 1)
scatter!(
ax, dot_x[mask], dot_y[mask];
color = CATEGORY_COLOR[cat],
markersize = 30,
strokewidth = 0,
label = "$cat — $(counts[i]) ($(pct)%)",
)
end
Legend(
fig[1, 2], ax, "Response";
labelcolor = INK,
titlecolor = INK,
framevisible = false,
backgroundcolor = PAGE_BG,
labelsize = 16,
titlesize = 18,
)
colsize!(fig.layout, 1, Relative(0.78))
# --- Save -------------------------------------------------------------------
save("plot-$(THEME).png", fig; px_per_unit = 2)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/dot-matrix-proportional/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": "dot-matrix-proportional",
"language": "julia",
"library": "makie",
"page": "https://anyplot.ai/dot-matrix-proportional/julia/makie",
"hub": "https://anyplot.ai/dot-matrix-proportional",
"code_json": "https://api.anyplot.ai/specs/dot-matrix-proportional/makie/code",
"spec_json": "https://api.anyplot.ai/specs/dot-matrix-proportional",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/dot-matrix-proportional/julia/makie/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/dot-matrix-proportional/julia/makie/plot-dark.png",
"quality_score": 93.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Dot Matrix Chart for Proportional Counts on anyplot.ai.