A sunburst chart displays hierarchical data as concentric rings, where each ring represents a level in the hierarchy. Inner rings show parent categories while outer rings show their children, with segment angles proportional to values. This radial visualization excels at revealing hierarchical structures and part-to-whole relationships across multiple levels simultaneously.
""" anyplot.ai
sunburst-basic: Basic Sunburst Chart
Library: letsplot 4.11.0 | Python 3.13.14
Quality: 85/100 | Updated: 2026-07-26
"""
import math
import os
import pandas as pd
from lets_plot import (
LetsPlot,
aes,
coord_fixed,
element_blank,
element_rect,
element_text,
geom_polygon,
geom_text,
ggplot,
ggsize,
labs,
layer_tooltips,
scale_fill_manual,
scale_x_continuous,
scale_y_continuous,
theme,
)
from lets_plot.export import ggsave
LetsPlot.setup_html()
# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
# Level 2/3 segments stay light pastels in both themes (only chrome flips), so their
# labels are fixed dark ink for contrast rather than the theme-adaptive INK token.
LABEL_ON_PASTEL = "#1A1A17"
# Data - Organizational budget by department, team, and project (3 levels)
data = [
# Engineering branch
{"level_1": "Eng", "level_2": "Backend", "level_3": "API", "value": 15},
{"level_1": "Eng", "level_2": "Backend", "level_3": "Database", "value": 10},
{"level_1": "Eng", "level_2": "Frontend", "level_3": "Web App", "value": 12},
{"level_1": "Eng", "level_2": "Frontend", "level_3": "Mobile", "value": 8},
# Sales branch
{"level_1": "Sales", "level_2": "North", "level_3": "Enterprise", "value": 18},
{"level_1": "Sales", "level_2": "North", "level_3": "SMB", "value": 7},
{"level_1": "Sales", "level_2": "South", "level_3": "Retail", "value": 9},
# Marketing branch
{"level_1": "Mktg", "level_2": "Digital", "level_3": "SEO", "value": 6},
{"level_1": "Mktg", "level_2": "Digital", "level_3": "Ads", "value": 8},
{"level_1": "Mktg", "level_2": "Brand", "level_3": "Events", "value": 7},
]
df = pd.DataFrame(data)
total_value = df["value"].sum()
def create_wedge(inner_r, outer_r, start_angle, end_angle, n_points=30):
angles_outer = [start_angle + (end_angle - start_angle) * i / n_points for i in range(n_points + 1)]
angles_inner = angles_outer[::-1]
x_outer = [outer_r * math.cos(a) for a in angles_outer]
y_outer = [outer_r * math.sin(a) for a in angles_outer]
x_inner = [inner_r * math.cos(a) for a in angles_inner]
y_inner = [inner_r * math.sin(a) for a in angles_inner]
return x_outer + x_inner, y_outer + y_inner
# Imprint palette branch colors for level 1; graduated lighter shades for levels 2-3
branch_colors = {
"Eng": "#009E73", # Imprint palette position 1
"Sales": "#C475FD", # Imprint palette position 2
"Mktg": "#4467A3", # Imprint palette position 3
}
level2_colors = {
"Backend": "#66C5AB", # Eng, ~40% lighter
"Frontend": "#80CFB9", # Eng, ~50% lighter
"North": "#E69E66", # Sales, ~40% lighter
"South": "#EEAF80", # Sales, ~50% lighter
"Digital": "#66AAD1", # Mktg, ~40% lighter
"Brand": "#80B9D9", # Mktg, ~50% lighter
}
level3_colors = {
"API": "#A6DDCE", # Eng, ~65% lighter
"Database": "#B3E2D5", # Eng, ~70% lighter
"Web App": "#BFE7DC", # Eng, ~75% lighter
"Mobile": "#CCECE3", # Eng, ~80% lighter
"Enterprise": "#F0C7A6", # Sales, ~65% lighter
"SMB": "#F2CFB3", # Sales, ~70% lighter
"Retail": "#F5D7BF", # Sales, ~75% lighter
"SEO": "#A6CEE4", # Mktg, ~65% lighter
"Ads": "#B3D5E8", # Mktg, ~70% lighter
"Events": "#BFDCEC", # Mktg, ~75% lighter
}
all_colors = {**branch_colors, **level2_colors, **level3_colors}
# Ring radii
r_inner_1, r_outer_1 = 0, 28 # Level 1 (innermost, filled center)
r_inner_2, r_outer_2 = 31, 52 # Level 2
r_inner_3, r_outer_3 = 55, 80 # Level 3 (outermost)
# Calculate proportions
level1_agg = df.groupby("level_1")["value"].sum().reset_index()
level1_agg["pct"] = level1_agg["value"] / total_value
level1_agg = level1_agg.sort_values("level_1").reset_index(drop=True)
level2_agg = df.groupby(["level_1", "level_2"])["value"].sum().reset_index()
level2_agg["pct"] = level2_agg["value"] / total_value
df["pct"] = df["value"] / total_value
# Build polygon and label data
polygon_rows = []
label_rows = []
segment_id = 0
start_angle = math.pi / 2 # Start at top, go clockwise
level1_angles = {}
for _, row in level1_agg.iterrows():
end_angle = start_angle - row["pct"] * 2 * math.pi
level1_angles[row["level_1"]] = {"start": start_angle, "end": end_angle}
x_pts, y_pts = create_wedge(r_inner_1, r_outer_1, end_angle, start_angle)
for x, y in zip(x_pts, y_pts, strict=True):
polygon_rows.append(
{
"x": x,
"y": y,
"segment_id": segment_id,
"color": row["level_1"],
"value": row["value"],
"pct": row["pct"],
}
)
mid_angle = (start_angle + end_angle) / 2
label_r = r_outer_1 * 0.55
label_rows.append(
{"x": label_r * math.cos(mid_angle), "y": label_r * math.sin(mid_angle), "label": row["level_1"], "level": 1}
)
segment_id += 1
start_angle = end_angle
level2_angles = {}
for level1_name in level1_agg["level_1"]:
l1_angles = level1_angles[level1_name]
l2_data = level2_agg[level2_agg["level_1"] == level1_name].sort_values("level_2")
cur_angle = l1_angles["start"]
for _, row in l2_data.iterrows():
end_angle = cur_angle - row["pct"] * 2 * math.pi
level2_angles[(row["level_1"], row["level_2"])] = {"start": cur_angle, "end": end_angle}
x_pts, y_pts = create_wedge(r_inner_2, r_outer_2, end_angle, cur_angle)
for x, y in zip(x_pts, y_pts, strict=True):
polygon_rows.append(
{
"x": x,
"y": y,
"segment_id": segment_id,
"color": row["level_2"],
"value": row["value"],
"pct": row["pct"],
}
)
mid_angle = (cur_angle + end_angle) / 2
label_r = (r_inner_2 + r_outer_2) / 2
label_rows.append(
{
"x": label_r * math.cos(mid_angle),
"y": label_r * math.sin(mid_angle),
"label": row["level_2"],
"level": 2,
}
)
segment_id += 1
cur_angle = end_angle
for level1_name in level1_agg["level_1"]:
l2_data = level2_agg[level2_agg["level_1"] == level1_name].sort_values("level_2")
for _, l2_row in l2_data.iterrows():
l2_key = (l2_row["level_1"], l2_row["level_2"])
l2_angles_range = level2_angles[l2_key]
l3_data = df[(df["level_1"] == l2_row["level_1"]) & (df["level_2"] == l2_row["level_2"])].sort_values("level_3")
cur_angle = l2_angles_range["start"]
for _, row in l3_data.iterrows():
end_angle = cur_angle - row["pct"] * 2 * math.pi
x_pts, y_pts = create_wedge(r_inner_3, r_outer_3, end_angle, cur_angle)
for x, y in zip(x_pts, y_pts, strict=True):
polygon_rows.append(
{
"x": x,
"y": y,
"segment_id": segment_id,
"color": row["level_3"],
"value": row["value"],
"pct": row["pct"],
}
)
mid_angle = (cur_angle + end_angle) / 2
label_r = (r_inner_3 + r_outer_3) / 2
label_rows.append(
{
"x": label_r * math.cos(mid_angle),
"y": label_r * math.sin(mid_angle),
"label": row["level_3"],
"level": 3,
}
)
segment_id += 1
cur_angle = end_angle
polygon_df = pd.DataFrame(polygon_rows)
label_df = pd.DataFrame(label_rows)
# Plot
plot = (
ggplot(polygon_df)
+ geom_polygon(
aes(x="x", y="y", fill="color", group="segment_id"),
color=PAGE_BG,
size=0.75,
alpha=0.9,
tooltips=layer_tooltips()
.line("@color")
.line("Budget|@value K")
.format("@pct", ".1%")
.line("Share of total|@pct"),
)
+ geom_text(
aes(x="x", y="y", label="label"),
data=label_df[label_df["level"] == 1],
size=6,
color="#FFFFFF",
fontface="bold",
)
+ geom_text(
aes(x="x", y="y", label="label"), data=label_df[label_df["level"] == 2], size=5.5, color=LABEL_ON_PASTEL
)
+ geom_text(
aes(x="x", y="y", label="label"), data=label_df[label_df["level"] == 3], size=4.5, color=LABEL_ON_PASTEL
)
+ scale_fill_manual(values=all_colors)
+ coord_fixed(ratio=1)
+ scale_x_continuous(limits=(-100, 100))
+ scale_y_continuous(limits=(-100, 100))
+ labs(
title="sunburst-basic · letsplot · anyplot.ai",
subtitle="Budget allocation by department, team, and project ($K)",
)
+ ggsize(600, 600)
+ theme(
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
panel_background=element_rect(fill=PAGE_BG),
plot_title=element_text(size=13, hjust=0.5, color=INK),
plot_subtitle=element_text(size=9, hjust=0.5, color=INK),
legend_position="none",
axis_title=element_blank(),
axis_text=element_blank(),
axis_ticks=element_blank(),
axis_line=element_blank(),
panel_grid=element_blank(),
)
)
# Save
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)
ggsave(plot, f"plot-{THEME}.html", path=".")
Part of Basic Sunburst Chart on anyplot.ai.