Scatter Plot with Marginal Distributions — ggplot2

A scatter plot enhanced with marginal distribution plots (histograms or kernel density estimates) on the top and right axes. This composite visualization simultaneously shows the bivariate relationship between two variables in the central scatter plot while displaying each variable's univariate distribution along its respective axis. It provides a comprehensive view of both the joint and marginal distributions in a single figure.

Scatter Plot with Marginal Distributions rendered with ggplot2

Renders

R source (ggplot2)

#' anyplot.ai
#' scatter-marginal: Scatter Plot with Marginal Distributions
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 91/100 | Created: 2026-09-09

library(ggplot2)
library(gridExtra)
library(ragg)

set.seed(42)

# --- Theme tokens ------------------------------------------------------------
THEME    <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG  <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
INK      <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
GRID     <- if (THEME == "light") "#CDCCC5" else "#454541"
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
                     "#AE3030", "#2ABCCD", "#954477", "#99B314")
BRAND <- IMPRINT_PALETTE[1]

# --- Data ----------------------------------------------------------------
# Annual rainfall vs. crop yield across 400 farm plots, moderately correlated.
n <- 400
rainfall_mm <- rnorm(n, mean = 800, sd = 150)
crop_yield_t_ha <- 1.5 + 0.0035 * rainfall_mm + rnorm(n, mean = 0, sd = 0.55)
df <- tibble::tibble(rainfall_mm = rainfall_mm, crop_yield_t_ha = crop_yield_t_ha)

x_range <- range(df$rainfall_mm)
y_range <- range(df$crop_yield_t_ha)

# --- Shared chrome ---------------------------------------------------------
anyplot_theme <- 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 = element_line(color = GRID, linewidth = 0.25),
    panel.grid.minor = element_blank(),
    axis.ticks       = element_blank()
  )

# --- Main scatter -----------------------------------------------------------
p_main <- ggplot(df, aes(rainfall_mm, crop_yield_t_ha)) +
  geom_point(color = BRAND, size = 2.4, alpha = 0.6, stroke = 0) +
  coord_cartesian(xlim = x_range, ylim = y_range) +
  labs(x = "Annual Rainfall (mm)", y = "Crop Yield (t/ha)") +
  anyplot_theme +
  theme(
    axis.line   = element_line(color = INK_SOFT, linewidth = 0.3),
    axis.title  = element_text(color = INK, size = 11),
    axis.text   = element_text(color = INK_SOFT, size = 10),
    plot.margin = margin(t = 4, r = 4, b = 10, l = 10)
  )

# --- Top marginal: rainfall distribution ------------------------------------
p_top <- ggplot(df, aes(rainfall_mm)) +
  geom_histogram(aes(y = after_stat(density)), bins = 30,
                  fill = BRAND, color = NA, alpha = 0.3) +
  geom_density(color = BRAND, linewidth = 0.6, alpha = 0.6) +
  coord_cartesian(xlim = x_range) +
  anyplot_theme +
  theme(
    axis.title  = element_blank(),
    axis.text   = element_blank(),
    plot.margin = margin(t = 10, r = 4, b = 2, l = 10)
  )

# --- Right marginal: crop yield distribution, flipped ------------------------
p_right <- ggplot(df, aes(crop_yield_t_ha)) +
  geom_histogram(aes(y = after_stat(density)), bins = 30,
                  fill = BRAND, color = NA, alpha = 0.3) +
  geom_density(color = BRAND, linewidth = 0.6, alpha = 0.6) +
  coord_flip(xlim = y_range) +
  anyplot_theme +
  theme(
    axis.title  = element_blank(),
    axis.text   = element_blank(),
    plot.margin = margin(t = 4, r = 10, b = 10, l = 2)
  )

# --- Align marginal panels to the main scatter's panel geometry -------------
g_main  <- ggplotGrob(p_main)
g_top   <- ggplotGrob(p_top)
g_right <- ggplotGrob(p_right)
g_top$widths    <- g_main$widths
g_right$heights <- g_main$heights

title_grob <- grid::textGrob(
  "scatter-marginal · r · ggplot2 · anyplot.ai",
  x = 0, hjust = 0,
  gp = grid::gpar(col = INK, fontsize = 12, fontface = "plain")
)

composite <- arrangeGrob(
  grobs = list(title_grob, g_top, g_main, g_right),
  layout_matrix = rbind(
    c(1, 1),
    c(2, NA),
    c(3, 4)
  ),
  widths  = c(4, 1),
  heights = c(0.5, 1, 4)
)

# --- Save --------------------------------------------------------------------
ggsave(
  filename = sprintf("plot-%s.png", THEME),
  plot     = composite,
  device   = ragg::agg_png,
  width    = 6,
  height   = 6,
  units    = "in",
  dpi      = 400,
  bg       = PAGE_BG
)

Retrieve this implementation

Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/scatter-marginal/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-marginal",
  "language": "r",
  "library": "ggplot2",
  "page": "https://anyplot.ai/scatter-marginal/r/ggplot2",
  "hub": "https://anyplot.ai/scatter-marginal",
  "code_json": "https://api.anyplot.ai/specs/scatter-marginal/ggplot2/code",
  "spec_json": "https://api.anyplot.ai/specs/scatter-marginal",
  "render_light_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-marginal/r/ggplot2/plot-light.png",
  "render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-marginal/r/ggplot2/plot-dark.png",
  "quality_score": 91.0,
  "license": "MIT",
  "guide": "https://anyplot.ai/llms.txt"
}

Part of Scatter Plot with Marginal Distributions on anyplot.ai.

Other implementations