The same plot in 14 other libraries — Python: Altair, Bokeh, 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: letsplot 4.11.0 | Python 3.13.15
Quality: 87/100 | Updated: 2026-09-30
"""
import os
import numpy as np
import pandas as pd
from lets_plot import (
LetsPlot,
aes,
element_blank,
element_line,
element_rect,
element_text,
geom_point,
ggplot,
ggsave,
ggsize,
ggtb,
guide_legend,
guides,
labs,
layer_tooltips,
scale_fill_manual,
scale_size_area,
scale_x_continuous,
theme,
theme_minimal,
)
LetsPlot.setup_html()
# 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"
RULE = "rgba(26,26,23,0.15)" if THEME == "light" else "rgba(240,239,232,0.15)"
# Imprint palette — 8 hues, theme-independent, hybrid-v3 sort
IMPRINT_PALETTE = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477", "#99B314"]
# Data - sports analytics: team payroll vs. win rate, bubble size = average attendance
np.random.seed(42)
conferences = ["Eastern", "Western"]
win_pct_offset = {"Eastern": 0.0, "Western": 5.0}
n_per_conference = 35
rows = []
for conference in conferences:
payroll_millions = np.random.uniform(90, 190, n_per_conference)
win_pct = np.clip(
18 + win_pct_offset[conference] + 0.28 * (payroll_millions - 90) + np.random.normal(0, 9, n_per_conference),
15,
78,
)
attendance_thousands = np.clip(np.random.normal(28, 7, n_per_conference), 12, 45)
for payroll, win, attendance in zip(payroll_millions, win_pct, attendance_thousands, strict=True):
rows.append({"payroll": payroll, "win_pct": win, "attendance": attendance, "conference": conference})
df = pd.DataFrame(rows)
# Plot
plot = (
ggplot(df, aes(x="payroll", y="win_pct", size="attendance", fill="conference"))
+ geom_point(
shape=21,
color=INK_SOFT,
stroke=0.4,
alpha=0.55,
tooltips=layer_tooltips()
.format("payroll", "${.0f}M")
.format("win_pct", "{.1f}%")
.format("attendance", "{.1f}K")
.line("@conference")
.line("Payroll|@payroll")
.line("Win Rate|@win_pct")
.line("Avg. Attendance|@attendance"),
)
+ scale_size_area(max_size=13, name="Avg. Attendance (K)", breaks=[15, 25, 35, 45])
+ scale_fill_manual(values=IMPRINT_PALETTE[:2], name="Conference")
+ scale_x_continuous(expand=[0.02, 5])
+ guides(
fill=guide_legend(nrow=1, override_aes={"size": 7}),
size=guide_legend(nrow=1, override_aes={"fill": IMPRINT_PALETTE[0], "color": INK_SOFT, "alpha": 0.55}),
)
+ labs(x="Team Payroll (Million USD)", y="Win Rate (%)", title="bubble-basic · python · letsplot · anyplot.ai")
+ theme_minimal()
+ theme(
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
# color must match fill explicitly: an unset color on panel_background
# renders a visible default border once a legend is present, even
# with panel_border=element_blank() (lets-plot 4.11.0 quirk).
panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
panel_border=element_blank(),
axis_title=element_text(size=13, color=INK),
axis_text=element_text(size=10, color=INK_SOFT),
plot_title=element_text(size=18, color=INK),
plot_margin=[30, 20, 20, 20],
legend_title=element_text(size=10, color=INK),
legend_text=element_text(size=10, color=INK_SOFT),
# color must match fill: legend frames are removed per the
# decoration-removal checklist (no visible box border).
legend_background=element_rect(fill=ELEVATED_BG, color=ELEVATED_BG),
panel_grid_major=element_line(size=0.3, color=RULE),
panel_grid_minor=element_blank(),
legend_position="bottom",
legend_box="horizontal",
legend_spacing=20,
)
+ ggsize(800, 450)
)
# Save: static PNG without the interactive toolbar, HTML with letsplot's
# distinctive pan/zoom toolbar (ggtb) layered on top for the interactive export
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)
ggsave(plot + ggtb(), f"plot-{THEME}.html", path=".")
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/bubble-basic/letsplot/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": "letsplot",
"page": "https://anyplot.ai/bubble-basic/python/letsplot",
"hub": "https://anyplot.ai/bubble-basic",
"code_json": "https://api.anyplot.ai/specs/bubble-basic/letsplot/code",
"spec_json": "https://api.anyplot.ai/specs/bubble-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/letsplot/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/letsplot/plot-dark.png",
"interactive_light_html": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/letsplot/plot-light.html",
"interactive_dark_html": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/python/letsplot/plot-dark.html",
"quality_score": 87.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Bubble Chart on anyplot.ai.