A ternary plot displays three-component compositional data on an equilateral triangle where each vertex represents 100% of one component. Points inside the triangle show compositions that sum to a constant total (usually 100%), with position indicating relative proportions. This visualization is essential for data where three variables are interdependent and constrained to sum to a fixed value.
""" anyplot.ai
ternary-basic: Basic Ternary Plot
Library: plotly 6.9.0 | Python 3.13.14
Quality: 91/100 | Updated: 2026-08-04
"""
import os
import numpy as np
import plotly.graph_objects as go
# Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome")
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
GRID = "rgba(26,26,23,0.12)" if THEME == "light" else "rgba(240,239,232,0.12)"
# Imprint palette (first series is always #009E73)
IMPRINT = [
"#009E73", # bluish green (brand — primary)
"#C475FD", # vermillion (secondary)
"#4467A3", # blue (tertiary)
"#BD8233", # reddish purple (quaternary)
]
# Data: three-way market share (leader / challenger / niche player) across
# four industries, each with a distinct competitive structure. This spreads
# points across the full simplex — concentrated markets sit near the "Leader"
# vertex, three-way races sit near the centroid, and duopolies sit near the
# leader-challenger edge — rather than clustering in one corner. Per-point
# noise is renormalized so the three shares always sum to exactly 100%.
np.random.seed(42)
industries = [
("Cloud Infrastructure", 65.0, 25.0, 10.0, "circle"),
("Streaming Video", 40.0, 35.0, 25.0, "diamond"),
("Ride-Hailing", 48.0, 45.0, 7.0, "square"),
("Food Delivery", 30.0, 50.0, 20.0, "triangle-up"),
]
n_per_industry = 11
leader_all, challenger_all, niche_all, industry_idx = [], [], [], []
for idx, (_name, lead0, chal0, niche0, _symbol) in enumerate(industries):
lead = np.clip(lead0 + np.random.normal(0, 5.0, n_per_industry), 1, None)
chal = np.clip(chal0 + np.random.normal(0, 5.0, n_per_industry), 1, None)
niche = np.clip(niche0 + np.random.normal(0, 3.0, n_per_industry), 1, None)
total = lead + chal + niche
leader_all.append(lead / total * 100)
challenger_all.append(chal / total * 100)
niche_all.append(niche / total * 100)
industry_idx.extend([idx] * n_per_industry)
leader_all = np.concatenate(leader_all)
challenger_all = np.concatenate(challenger_all)
niche_all = np.concatenate(niche_all)
industry_idx = np.array(industry_idx)
title_text = "Market Share by Industry · ternary-basic · python · plotly · anyplot.ai"
title_fontsize = round(16 * min(1.0, 67 / len(title_text)))
fig = go.Figure()
# One trace per industry: color AND marker symbol both encode the group, so
# the grouping reads even for viewers who can't distinguish the hues.
for idx, (name, _lead0, _chal0, _niche0, symbol) in enumerate(industries):
mask = industry_idx == idx
fig.add_trace(
go.Scatterternary(
a=leader_all[mask],
b=challenger_all[mask],
c=niche_all[mask],
mode="markers",
name=name,
marker={
"symbol": symbol,
"size": 15,
"color": IMPRINT[idx],
"opacity": 0.82,
"line": {"width": 1.5, "color": PAGE_BG},
},
hovertemplate=(
"<b>%{customdata}</b><br>Leader: %{a:.1f}%<br>Challenger: %{b:.1f}%<br>Niche: %{c:.1f}%<extra></extra>"
),
customdata=[name] * int(mask.sum()),
)
)
# Reference line: the 50% "majority" threshold — above it the leader alone
# controls the market, below it no single player commands a majority. A
# domain-specific annotation, not just decoration.
fig.add_trace(
go.Scatterternary(
a=[50, 50],
b=[50, 0],
c=[0, 50],
mode="lines",
line={"width": 1.5, "color": INK_SOFT, "dash": "dot"},
showlegend=False,
hoverinfo="skip",
)
)
fig.add_annotation(
text="- - - dashed line: 50% majority threshold",
xref="paper",
yref="paper",
x=0.0,
y=0.87,
xanchor="left",
yanchor="bottom",
showarrow=False,
font={"size": 13, "color": INK_SOFT},
)
fig.update_layout(
autosize=False,
title={"text": title_text, "font": {"size": title_fontsize, "color": INK}, "x": 0.5, "xanchor": "center"},
ternary={
"sum": 100,
"aaxis": {
"title": {"text": "Market Leader (%)", "font": {"size": 12, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 10, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"baxis": {
"title": {"text": "Challenger (%)", "font": {"size": 12, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 10, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"caxis": {
"title": {"text": "Niche Player (%)", "font": {"size": 12, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 10, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"bgcolor": PAGE_BG,
},
paper_bgcolor=PAGE_BG,
plot_bgcolor=PAGE_BG,
margin={"l": 90, "r": 90, "t": 100, "b": 80},
legend={
"title": {"text": "Industry", "font": {"size": 11, "color": INK}},
"x": 0.98,
"y": 0.02,
"xanchor": "right",
"yanchor": "bottom",
"bgcolor": ELEVATED_BG,
"bordercolor": INK_SOFT,
"borderwidth": 1,
"font": {"color": INK_SOFT, "size": 10},
},
)
# Save outputs — hard target 3200x1800, see prompts/library/plotly.md "Canvas"
fig.write_image(f"plot-{THEME}.png", width=800, height=450, scale=4)
fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/ternary-basic/plotly/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": "ternary-basic",
"language": "python",
"library": "plotly",
"page": "https://anyplot.ai/ternary-basic/python/plotly",
"hub": "https://anyplot.ai/ternary-basic",
"code_json": "https://api.anyplot.ai/specs/ternary-basic/plotly/code",
"spec_json": "https://api.anyplot.ai/specs/ternary-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/ternary-basic/python/plotly/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/ternary-basic/python/plotly/plot-dark.png",
"interactive_light_html": "https://storage.googleapis.com/anyplot-images/plots/ternary-basic/python/plotly/plot-light.html",
"interactive_dark_html": "https://storage.googleapis.com/anyplot-images/plots/ternary-basic/python/plotly/plot-dark.html",
"quality_score": 91.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Ternary Plot on anyplot.ai.