A nested donut chart displays hierarchical data as multiple concentric rings, where each ring represents a level of the hierarchy. Inner rings show parent categories while outer rings show their subdivisions. This visualization effectively reveals part-to-whole relationships across multiple levels while maintaining the familiar donut format.

""" anyplot.ai
donut-nested: Nested Donut Chart
Library: plotly 6.7.0 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-08
"""
import os
import plotly.graph_objects as go
# Theme tokens (see prompts/default-style-guide.md)
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"
# Okabe-Ito categorical palette (canonical order, positions 1-4 for inner ring)
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233"]
def lighten_hex(hex_color, factor=0.4):
"""Create a lighter shade of a hex color by blending with white."""
hex_color = hex_color.lstrip("#")
r, g, b = tuple(int(hex_color[i : i + 2], 16) for i in (0, 2, 4))
r = int(r + (255 - r) * factor)
g = int(g + (255 - g) * factor)
b = int(b + (255 - b) * factor)
return f"#{r:02x}{g:02x}{b:02x}"
# Data - Company budget allocation by department and expense category
departments = ["Engineering", "Marketing", "Sales", "Operations"]
dept_values = [45, 25, 18, 12] # Millions
dept_colors = IMPRINT
# Child categories (outer ring) with consistent color families (lighter shades)
categories = [
# Engineering
"Salaries",
"Infrastructure",
"R&D",
"Tools",
# Marketing
"Advertising",
"Events",
"Content",
# Sales
"Commissions",
"Travel",
"Training",
# Operations
"Facilities",
"IT Support",
]
cat_values = [
# Engineering: 45M total
22,
12,
8,
3,
# Marketing: 25M total
14,
7,
4,
# Sales: 18M total
10,
5,
3,
# Operations: 12M total
8,
4,
]
# Generate child colors as lighter shades of parent colors
cat_colors = []
child_counts = [4, 3, 3, 2] # Children per department
for dept_idx, count in enumerate(child_counts):
base_color = dept_colors[dept_idx]
for i in range(count):
# Create progressively lighter shades
shade = lighten_hex(base_color, factor=0.15 + i * 0.15)
cat_colors.append(shade)
# Create figure with two pie traces (inner and outer rings)
fig = go.Figure()
# Inner ring - Departments (parent categories) with both name and percentage
fig.add_trace(
go.Pie(
values=dept_values,
labels=departments,
hole=0.30,
domain={"x": [0.12, 0.72], "y": [0.05, 0.95]},
marker={"colors": dept_colors, "line": {"color": PAGE_BG, "width": 3}},
textinfo="label+percent",
textposition="inside",
textfont={"size": 18, "color": "white"},
hovertemplate="<b>%{label}</b><br>$%{value}M<br>%{percent}<extra></extra>",
name="Departments",
sort=False,
)
)
# Outer ring - Expense categories (child categories)
fig.add_trace(
go.Pie(
values=cat_values,
labels=categories,
hole=0.58,
domain={"x": [0.12, 0.72], "y": [0.05, 0.95]},
marker={"colors": cat_colors, "line": {"color": PAGE_BG, "width": 2}},
textinfo="label",
textposition="outside",
textfont={"size": 15, "color": INK},
hovertemplate="<b>%{label}</b><br>$%{value}M<br>%{percent}<extra></extra>",
name="Categories",
sort=False,
)
)
# Layout with theme-adaptive colors
fig.update_layout(
title={
"text": "Company Budget Allocation · donut-nested · plotly · pyplots.ai",
"font": {"size": 28, "color": INK},
"x": 0.5,
"xanchor": "center",
},
showlegend=True,
legend={
"font": {"size": 16, "color": INK_SOFT},
"orientation": "v",
"x": 1.02,
"y": 0.5,
"yanchor": "middle",
"bgcolor": ELEVATED_BG,
"bordercolor": INK_SOFT,
"borderwidth": 1,
},
paper_bgcolor=PAGE_BG,
plot_bgcolor=PAGE_BG,
font={"color": INK},
margin={"l": 80, "r": 200, "t": 100, "b": 80},
annotations=[
{
"text": "<b>$100M</b><br>Total Budget",
"x": 0.42,
"y": 0.5,
"font": {"size": 24, "color": INK},
"showarrow": False,
}
],
)
# Save as PNG (4800 x 2700 px)
fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
# Save interactive HTML
fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")
Part of Nested Donut Chart on anyplot.ai.