Gallery
Live, touchable charts — not thumbnails. Hover any of them to see the
crosshair track; each is the exact same @pond-ts/charts primitives you'd
compose yourself. Build it → opens the chart's own page — where the data
came from, the minimal version in 10–20 lines, and the knobs worth trying.
Story ↗ jumps to its full Storybook coverage (every prop, every variant).
Grouped by domain, because "can this library draw my thing?" is usually asked from inside a problem. If you're shopping by shape instead, the chart-type reference is the index by primitive.
- Ops & infrastructure
- Finance
- Weather & climate
- Energy
- Fitness & health
- Science & measurement
- Product, transport & statistical
Ops & infrastructure
Where most evaluators start: hosts, latency, error budgets, and the incident you're explaining on Monday.
Finance
Market time is not wall-clock time, so these charts sit on a trading calendar: the weekends, the ten holidays and the two half-days are collapsed out of the axis rather than drawn as dead space. Candles, a volume row, a study's appended columns and a derived curve — the same four primitives you'd compose yourself.
The prices are modelled, not measured. Every feed worth having forbids redistribution, so rather than quietly ship someone's bars these run on a seeded process model — opening gaps, volatility clustering, regimes, volume that answers price. The session calendar is real; the prices are not.
Weather & climate
The domain with the best public data — every card here draws measured NOAA or NASA numbers, not a model of them. Three of the four are one airport's 2024: the same station asked about its temperature, its rain and its wind.
Energy
Grid data is where composition, crossover and signed values all turn up at once. The first three cards are the same real weekend — Easter 2025 in Germany, the quietest demand day of the year meeting a big solar peak. The last two are a different grid on a stranger evening — Spain, during the total solar eclipse of 12 August 2026: what demand did, and what solar did.
Fitness & health
Activity data is the awkward case every charting library gets asked about: irregular sampling, dropouts where the sensor coasted, and a duration axis rather than a wall-clock one.
Science & measurement
Instruments, and what they record: a buoy, a seismometer, a tide gauge, an air monitor and a satellite record of one patch of the Pacific. All five datasets here are real, measured, public-domain observations — nothing modelled — and between them they cover the axis that isn't time, the trace that's denser than the screen, the reading that only means something next to a threshold, and the year that isn't finished yet.
Product, transport & statistical
Counting what people make and do. The first card here is as meta as it gets: the library's own repository, drawn by the library.
Where these come from
Every card above is one of the chart-type support matrix's
draw layers, seeded with deterministic sample data (no Math.random(), no
Date.now() — what you see is what renders on every visit). None of it is a
special "demo mode": the same ChartContainer / ChartRow / Layers composition
you'd write yourself, mounted for real. Fixture provenance — where each dataset
came from, its licence, and what was dropped — lives in each fixture's header
(the conventions are in
src/examples/lib/README.md).
The cards that move share one animation loop, animate only while they're on screen, and hold a still frame if your system asks for reduced motion.
- Storybook — the systematic, per-prop knob walk each card's Story link jumps into.
- Using @pond-ts/charts — install notes and integration gotchas.
- Theming — the
ChartThememodel behind every card here (they all run the docs site's own live theme,useSiteChartTheme).