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 Scatter Plot in Python, R, Julia and JavaScript.
A fundamental 2D scatter plot that displays the relationship between two numeric variables by plotting points on a Cartesian coordinate system. This visualization is essential for exploring correlations, identifying patterns, detecting outliers, and understanding the distribution of paired data points.
#' anyplot.ai
#' scatter-basic: Basic Scatter Plot
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 90/100 | Updated: 2026-06-25
library(ggplot2)
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"
# Approximate RULE (15% opacity INK blended over PAGE_BG) — ggplot2 lacks rgba
GRID_LINE <- if (THEME == "light") "#D8D7D0" else "#3A3A36"
# Imprint palette — canonical order
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314")
# Data — marketing spend vs quarterly revenue across 200 campaigns
n <- 200
spend <- runif(n, 5, 150)
revenue <- 3.5 * spend + 80 + rnorm(n, 0, 150)
revenue <- pmax(revenue, 10)
df <- data.frame(spend = spend, revenue = revenue)
# Pearson r for bottom-right annotation
r_val <- cor(df$spend, df$revenue)
r_label <- sprintf("Pearson r = %.2f", round(r_val, 2))
# Plot
p <- ggplot(df, aes(x = spend, y = revenue)) +
geom_smooth(
method = "lm",
se = TRUE,
color = IMPRINT_PALETTE[1],
fill = IMPRINT_PALETTE[1],
alpha = 0.15,
linewidth = 1.0
) +
geom_point(
color = IMPRINT_PALETTE[1],
size = 2.5,
alpha = 0.7,
shape = 16
) +
annotate(
geom = "text",
x = max(df$spend),
y = min(df$revenue) + 5,
label = r_label,
color = INK_SOFT,
size = 3,
fontface = "italic",
hjust = 1
) +
labs(
title = "scatter-basic · r · ggplot2 · anyplot.ai",
x = "Marketing Spend ($K)",
y = "Quarterly Revenue ($K)"
) +
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.border = element_blank(),
panel.grid.major = element_line(color = GRID_LINE, linewidth = 0.3),
panel.grid.minor = element_blank(),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
axis.line = element_line(color = INK_SOFT, linewidth = 0.5),
axis.ticks = element_blank(),
plot.title = element_text(color = INK, size = 12,
face = "bold", margin = margin(b = 12)),
plot.margin = margin(20, 20, 20, 20)
)
# Save — 3200×1800 px (landscape 16:9)
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/scatter-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": "scatter-basic",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/scatter-basic/r/ggplot2",
"hub": "https://anyplot.ai/scatter-basic",
"code_json": "https://api.anyplot.ai/specs/scatter-basic/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/scatter-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-basic/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-basic/r/ggplot2/plot-dark.png",
"quality_score": 90.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Scatter Plot on anyplot.ai.