A cumulative histogram (also known as an ogive or cumulative frequency histogram) displays the running total of observations up to each bin boundary. The y-axis shows cumulative count or proportion, creating a monotonically increasing step function that reaches the total sample size (or 1.0 for normalized).
#' anyplot.ai
#' histogram-cumulative: Cumulative Histogram
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 84/100 | Created: 2026-09-05
library(ggplot2)
library(ragg)
set.seed(42)
# --- Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome") ----
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"
BRAND <- "#009E73" # Imprint palette position 1 — always first series
# --- Data: net fill weight of cereal boxes on a packaging line (target 500 g) ----
box_weights <- rnorm(600, mean = 500, sd = 9)
bin_width <- 3
breaks <- seq(
floor(min(box_weights) / bin_width) * bin_width,
ceiling(max(box_weights) / bin_width) * bin_width,
by = bin_width
)
counts <- hist(box_weights, breaks = breaks, plot = FALSE)$counts
# Right bin edge + running total up to that edge; the leading zero anchors the
# step at the histogram's left boundary so geom_step starts from the ground.
cum_df <- data.frame(
weight = c(breaks[1], breaks[-1]),
cum_count = c(0, cumsum(counts))
)
n_total <- length(box_weights)
# --- Plot -------------------------------------------------------------------
x_max <- max(cum_df$weight)
p <- ggplot(cum_df, aes(x = weight, y = cum_count)) +
geom_hline(yintercept = n_total, linetype = "dashed", color = BRAND, linewidth = 0.6, alpha = 0.45) +
geom_step(color = BRAND, linewidth = 1.1, direction = "hv") +
geom_point(data = cum_df[-1, ], color = BRAND, size = 2.75) +
annotate(
"text",
x = x_max, y = n_total, label = sprintf("Total (n = %d)", n_total),
color = INK_SOFT, size = 2.8, hjust = 1, vjust = -0.7
) +
labs(
title = "histogram-cumulative · r · ggplot2 · anyplot.ai",
x = "Box fill weight (g)",
y = "Cumulative count"
) +
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_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.y = element_line(color = INK, linewidth = 0.25),
axis.line = element_line(color = INK_SOFT),
axis.ticks = 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)
)
# --- Save (PNG, both themes) --------------------------------------------------
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/histogram-cumulative/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": "histogram-cumulative",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/histogram-cumulative/r/ggplot2",
"hub": "https://anyplot.ai/histogram-cumulative",
"code_json": "https://api.anyplot.ai/specs/histogram-cumulative/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/histogram-cumulative",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/histogram-cumulative/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/histogram-cumulative/r/ggplot2/plot-dark.png",
"quality_score": 84.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Cumulative Histogram on anyplot.ai.