The same plot in 14 other libraries — Python: Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts. Compare all 15 side by side: Basic Bubble Chart in Python, R, Julia and JavaScript.
A bubble chart extending scatter plots by adding a third dimension through bubble size. Each point's position shows two variables (x, y) while the bubble size represents a third quantitative variable. This visualization is excellent for understanding relationships between three numerical variables simultaneously, revealing patterns that would be hidden in traditional 2D scatter plots.
""" anyplot.ai
bubble-basic: Basic Bubble Chart
Library: altair 6.3.0 | Python 3.13.15
Quality: 91/100 | Created: 2026-09-30
"""
import os
import altair as alt
import numpy as np
import pandas as pd
from PIL import Image
# Theme tokens
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"
# Imprint palette (canonical order)
IMPRINT_PALETTE = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477", "#99B314"]
stage_colors = IMPRINT_PALETTE[:4]
# Data — tech startup metrics: funding vs revenue, sized by segment share, colored by stage
np.random.seed(42)
n = 49
stages = np.random.choice(["Seed", "Series A", "Series B", "Growth"], size=n, p=[0.25, 0.30, 0.25, 0.20])
stage_funding = {"Seed": (6, 3.5), "Series A": (15, 5.5), "Series B": (40, 9), "Growth": (60, 12)}
funding_m = np.array([np.random.normal(*stage_funding[s]) for s in stages])
funding_m = np.clip(funding_m, 1, 80)
revenue_m = funding_m * np.random.uniform(0.6, 1.6, size=n) + np.random.normal(5, 3.5, size=n)
revenue_m = np.clip(revenue_m, 2, 118)
# Segment share (%) of each company's own addressable segment, not a single global
# market — so per-stage totals need not sum to 100%. Drawn independently of Stage
# (a single wide distribution) so bubble size carries genuinely new information
# rather than tracking the color-encoded cohort.
market_share = np.clip(np.random.normal(30, 13, size=n), 8, 62)
df = pd.DataFrame(
{
"Funding ($M)": np.round(funding_m, 1),
"Revenue ($M)": np.round(revenue_m, 1),
"Segment Share (%)": np.round(market_share, 1),
"Stage": pd.Categorical(stages, categories=["Seed", "Series A", "Series B", "Growth"], ordered=True),
}
)
# Add two counter-examples so funding and revenue don't form a single
# near-linear cloud: a high-funded, low-revenue laggard, and a
# capital-efficient, low-funded high-revenue climber.
outlier_laggard = pd.DataFrame(
{
"Funding ($M)": [68.5],
"Revenue ($M)": [7.2],
"Segment Share (%)": [22.0],
"Stage": pd.Categorical(["Series B"], categories=["Seed", "Series A", "Series B", "Growth"], ordered=True),
}
)
outlier_climber = pd.DataFrame(
{
"Funding ($M)": [11.0],
"Revenue ($M)": [54.0],
"Segment Share (%)": [31.0],
"Stage": pd.Categorical(["Series A"], categories=["Seed", "Series A", "Series B", "Growth"], ordered=True),
}
)
df = pd.concat([df, outlier_laggard, outlier_climber], ignore_index=True)
title = "bubble-basic · python · altair · anyplot.ai"
# Legend-bound point selection — clicking a Stage in the legend spotlights that
# cohort by dimming the rest, an interactive capability distinctive to Altair's
# Vega-Lite selection grammar (preserved in the saved interactive HTML). The
# default "select all" state renders every bubble at the same 0.5 opacity, so
# the static PNG shows no highlight — only the saved HTML is interactive.
stage_selection = alt.selection_point(fields=["Stage"], bind="legend")
# Plot — bubble layer
bubbles = (
alt.Chart(df)
.mark_circle(stroke=PAGE_BG, strokeWidth=2)
.encode(
order=alt.Order(
"Segment Share (%):Q", sort="descending"
), # largest bubbles drawn first (behind), smallest on top so overlapping clusters stay legible
x=alt.X(
"Funding ($M):Q", scale=alt.Scale(domain=[0, 85], nice=False), axis=alt.Axis(domain=False, ticks=False)
),
y=alt.Y(
"Revenue ($M):Q", scale=alt.Scale(domain=[0, 125], nice=False), axis=alt.Axis(domain=False, ticks=False)
),
size=alt.Size(
"Segment Share (%):Q",
scale=alt.Scale(range=[50, 1500], domain=[8, 62]),
legend=alt.Legend(
title="Segment Share (%)",
titleFontSize=11,
labelFontSize=12,
values=[10, 25, 40, 55],
symbolFillColor=INK_SOFT, # neutral fill (not a categorical hue) - the size legend applies to every Stage, not just Seed
symbolStrokeColor=PAGE_BG,
symbolOpacity=0.65,
direction="vertical",
),
),
color=alt.Color(
"Stage:N",
scale=alt.Scale(domain=["Seed", "Series A", "Series B", "Growth"], range=stage_colors),
legend=alt.Legend(
title="Stage",
titleFontSize=11,
labelFontSize=12,
symbolType="circle",
symbolSize=200,
symbolStrokeWidth=0,
symbolOpacity=0.65,
),
),
opacity=alt.condition(stage_selection, alt.value(0.5), alt.value(0.1)),
tooltip=["Stage:N", "Funding ($M):Q", "Revenue ($M):Q", "Segment Share (%):Q"],
)
.add_params(stage_selection)
)
chart = (
bubbles.properties(
width=620,
height=320,
background=PAGE_BG,
padding={"left": 0, "right": 0, "top": 0, "bottom": 0},
title=alt.Title(
title,
fontSize=16,
fontWeight="bold",
color=INK,
anchor="middle",
subtitle="Tech Startup Metrics — Funding vs Revenue by Stage & Segment Share",
subtitleFontSize=12,
subtitleColor=INK_SOFT,
subtitlePadding=4,
),
)
.configure_view(fill=PAGE_BG, strokeWidth=0, continuousWidth=620, continuousHeight=320)
.configure_axis(
tickColor=INK_SOFT,
gridColor=INK,
gridOpacity=0.15,
labelColor=INK_SOFT,
titleColor=INK,
labelFontSize=12,
titleFontSize=12,
)
.configure_legend(
fillColor=ELEVATED_BG, strokeWidth=0, labelColor=INK_SOFT, titleColor=INK, orient="right", padding=10
)
)
# Save PNG
chart.save(f"plot-{THEME}.png", scale_factor=4.0)
# PAD to exact 3200×1800 (do not crop — cropping clips title/axis labels)
TW, TH = 3200, 1800
_img = Image.open(f"plot-{THEME}.png").convert("RGB")
_w, _h = _img.size
if _w > TW or _h > TH:
raise SystemExit(
f"altair vl-convert produced {_w}×{_h}, exceeds target {TW}×{TH}. "
f"Shrink chart .properties(width=, height=) values and re-render."
)
if _w < TW or _h < TH:
_canvas = Image.new("RGB", (TW, TH), PAGE_BG)
_canvas.paste(_img, ((TW - _w) // 2, (TH - _h) // 2))
_canvas.save(f"plot-{THEME}.png")
# Save HTML
chart.save(f"plot-{THEME}.html")
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/bubble-basic/altair/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": "bubble-basic",
"language": "python",
"library": "altair",
"page": "https://anyplot.ai/bubble-basic/python/altair",
"hub": "https://anyplot.ai/bubble-basic",
"code_json": "https://api.anyplot.ai/specs/bubble-basic/altair/code",
"spec_json": "https://api.anyplot.ai/specs/bubble-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/altair/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/altair/plot-dark.png",
"interactive_light_html": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/altair/plot-light.html",
"interactive_dark_html": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/altair/plot-dark.html",
"quality_score": 91.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Bubble Chart on anyplot.ai.