The same plot in 14 other libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; 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: ggplot2 3.5.1 | R 4.4.1
#' Quality: 76/100 | Updated: 2026-09-30
library(ggplot2)
library(dplyr)
library(scales)
library(ragg)
set.seed(42)
# Theme tokens
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
GRID <- if (THEME == "light") "#D3D1CA" else "#3A3A37"
# Slot 5 (#AE3030, matte red) is the deferred semantic anchor for bad/loss/
# error — there's no such category here, so Sporting Goods takes slot 6
# (cyan) instead of spending red on an ordinary category.
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233", "#2ABCCD")
# Data — synthetic retail product-portfolio scenario: customer satisfaction
# score vs. average retail price, bubble = monthly sales volume, colored by
# product category. Price bands are the dimension that keeps the five
# categories visually separated (satisfaction scores alone overlap a lot more
# across categories than price does), which avoids stacking every category
# into one dense cluster.
n_per_category <- 22
category_params <- tibble::tibble(
category = c("Consumer Electronics", "Apparel & Footwear", "Home & Kitchen", "Beauty & Personal Care", "Sporting Goods"),
code = c("ELEC", "APRL", "HOMK", "BEAU", "SPRT"),
quality_mu = c(74, 66, 79, 84, 70),
quality_sd = c(8, 9, 7, 6, 8),
price_mu = c(280, 52, 90, 36, 130),
price_sd = c(70, 10, 22, 7, 35),
sales_meanlog = log(c(22, 68, 40, 75, 30)),
sales_sd = c(0.30, 0.28, 0.32, 0.28, 0.32)
)
# Flat, vectorized generation: repeat each category's params n_per_category
# times, then draw all rows in one rnorm()/rlnorm() call each (both accept
# vectorized mean/sd arguments) instead of looping per category.
row_params <- category_params[rep(seq_len(nrow(category_params)), each = n_per_category), ]
n_total <- nrow(row_params)
products <- tibble::tibble(
category = row_params$category,
satisfaction = pmin(98, pmax(35, rnorm(n_total, mean = row_params$quality_mu, sd = row_params$quality_sd))),
price = pmin(650, pmax(22, rnorm(n_total, mean = row_params$price_mu, sd = row_params$price_sd))),
sales_volume = pmin(100, pmax(10, rlnorm(n_total, meanlog = row_params$sales_meanlog, sdlog = row_params$sales_sd)))
) |>
dplyr::mutate(category = factor(category, levels = category_params$category)) |>
# Draw largest bubbles first (bottom layer) so smaller bubbles stay
# visible on top instead of being buried under high-volume sellers.
dplyr::arrange(dplyr::desc(sales_volume))
category_colors <- stats::setNames(IMPRINT_PALETTE, levels(products$category))
# Bubble-size domain floor: anchoring scale_size_area() at an absolute zero
# buries the smallest real values at a couple of visible pixels. Flooring the
# lower limit just below the observed minimum keeps sizing strictly area-true
# across the data range while giving the smallest bubbles real presence.
sales_range <- range(products$sales_volume)
size_limits <- c(sales_range[1] * 0.75, sales_range[2])
# Plot
p <- ggplot(products, aes(
x = satisfaction,
y = price,
size = sales_volume,
fill = category
)) +
geom_point(
shape = 21,
color = PAGE_BG,
alpha = 0.42,
stroke = 1.0
) +
scale_x_continuous(
breaks = seq(40, 100, 10),
expand = expansion(mult = c(0.08, 0.06))
) +
scale_y_continuous(
breaks = seq(0, 600, 100),
labels = label_dollar(),
expand = expansion(mult = c(0.08, 0.08))
) +
scale_size_area(
max_size = 13,
limits = size_limits,
breaks = c(10, 40, 70, 100),
labels = c("10", "40", "70", "100"),
name = "Monthly Sales Volume (K units)"
) +
scale_fill_manual(values = category_colors, name = "Product Category") +
labs(
title = "bubble-basic · r · ggplot2 · anyplot.ai",
subtitle = "Bubble size encodes monthly sales volume",
x = "Customer Satisfaction Score (0-100)",
y = "Average Retail Price"
) +
guides(
fill = guide_legend(override.aes = list(size = 4, alpha = 0.9))
) +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major.x = element_line(color = GRID, linewidth = 0.25),
panel.grid.major.y = element_line(color = GRID, linewidth = 0.25),
panel.grid.minor = element_blank(),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
plot.title = element_text(color = INK, size = 12),
plot.subtitle = element_text(color = INK_SOFT, size = 9, margin = margin(b = 8)),
legend.background = element_rect(fill = ELEVATED_BG, color = NA),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 10),
legend.key = element_rect(fill = NA, color = NA),
legend.key.size = unit(0.35, "cm"),
legend.key.spacing.y = unit(1, "pt"),
legend.spacing.y = unit(2, "pt"),
legend.justification.right = "center",
legend.margin = margin(4, 6, 4, 6),
legend.box.spacing = unit(6, "pt"),
plot.margin = margin(12, 12, 10, 10)
)
# Save
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/bubble-basic/ggplot2/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": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/bubble-basic/r/ggplot2",
"hub": "https://anyplot.ai/bubble-basic",
"code_json": "https://api.anyplot.ai/specs/bubble-basic/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/bubble-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/bubble-basic/r/ggplot2/plot-dark.png",
"quality_score": 76.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Bubble Chart on anyplot.ai.