Histogram
Bin a sample of scalar observations into equal-width buckets and
emit one bar per bin. The default binning rule is the square-root
rule (⌈√n⌉); pass BinCount::Fixed(n) for a fixed bin count.
The demo plots heights of Union Army recruits, c. 1864, drawn from Benjamin A. Gould's 1869 Investigations in the Military and Anthropological Statistics of American Soldiers — the largest systematic anthropometric study of the 19th century. The distribution centres on 67.8 in (~172 cm) with σ ≈ 2.5 in, the Gaussian fit Gould reported for the 25–34 age bracket, and later anchored Galton's work on regression to the mean.
Source: Anthropometric history — Wikipedia
Public surface
use wisp_chart::distributions::{BinCount, Histogram};
let samples: Vec<f32> = collect_observations();
let hist = Histogram::from_samples(
&samples,
BinCount::Auto, // sqrt-rule
Some((0.0, 100.0)), // optional clamping extent
);
let g = hist.emit_graphics(&theme, Vec2::new(360.0, 240.0));BinCount::Auto—⌈√n⌉bins. Cheap, robust, biased toward over-binning for very large samples.BinCount::Fixed(k)— explicit bin count. Use when comparing multiple histograms side-by-side so the bars line up.
A histogram shows you exactly which observations landed where — useful for outlier hunting and reading off exact counts. A KDE shows you the underlying density estimate — useful when the bin-edge choice would distort the story. They compose; some teams ship both stacked.