From fabrik
Guides building exploratory data visualizations with Observable Plot, a D3-based JavaScript library. Covers marks like dots, lines, bars; scales, transforms for charts.
How this skill is triggered — by the user, by Claude, or both
Slash command
/fabrik:observable-plotThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Observable Plot is a JavaScript library for exploratory data visualization. It's built on D3 and provides a concise, declarative API for creating charts.
features/curves.mdfeatures/facets.mdfeatures/interactions.mdfeatures/intervals.mdfeatures/legends.mdfeatures/markers.mdfeatures/projections.mdfeatures/scales.mdfeatures/shorthand.mdmarks/area.mdmarks/arrow.mdmarks/auto.mdmarks/axis.mdmarks/bar.mdmarks/bollinger.mdmarks/box.mdmarks/cell.mdmarks/contour.mdmarks/crosshair.mdmarks/delaunay.mdObservable Plot is a JavaScript library for exploratory data visualization. It's built on D3 and provides a concise, declarative API for creating charts.
npm install @observablehq/plot
Or via CDN:
<script type="module">
import * as Plot from "https://cdn.jsdelivr.net/npm/@observablehq/[email protected]/+esm";
</script>
The main function that renders a visualization. Returns an SVG or HTML figure element.
Plot.plot({
marks: [
Plot.dot(data, {x: "weight", y: "height"})
]
})
| Option | Description | Default |
|---|---|---|
width | Outer width in pixels | 640 |
height | Outer height in pixels | auto |
margin | All margins | varies |
marginTop/Right/Bottom/Left | Individual margins | varies |
marks | Array of marks to render | required |
color | Color scale options | auto |
x, y | Position scale options | auto |
title, subtitle | Chart titles | none |
caption | Figure caption | none |
Plot expects tabular data as arrays of objects:
const data = [
{date: new Date("2024-01-01"), value: 100, category: "A"},
{date: new Date("2024-01-02"), value: 120, category: "B"}
];
Map data columns to visual properties:
Plot.dot(data, {
x: "date", // column name
y: "value", // column name
fill: "category", // color by category
r: 5 // constant radius
})
Plot.lineY(data, {x: "date", y: "value"}).plot()
Plot.barY(data, {x: "category", y: "value"}).plot()
Plot.dot(data, {x: "weight", y: "height", fill: "species"}).plot()
Plot.rectY(data, Plot.binX({y: "count"}, {x: "value"})).plot()
Plot.areaY(data, {x: "date", y: "value", fill: "steelblue"}).plot()
This skill includes detailed documentation for each feature:
marks/area.md - Area charts and stacked areasmarks/bar.md - Bar charts (horizontal and vertical)marks/dot.md - Scatter plots and bubble chartsmarks/line.md - Line chartsmarks/rect.md - Rectangles, histograms, heatmapsmarks/text.md - Text labels and annotationsmarks/rule.md - Reference linesmarks/cell.md - Heatmaps with ordinal dimensionsmarks/tip.md - Interactive tooltipsmarks/axis.md - Custom axesmarks/geo.md - Geographic/map visualizationsmarks/link.md - Connections between pointsmarks/arrow.md - Directed arrowsmarks/vector.md - Vector fieldsmarks/tick.md - Tick marksmarks/box.md - Box plotsmarks/frame.md - Frame decorationmarks/image.md - Image glyphsmarks/contour.md - Contour plotsmarks/density.md - Density estimationmarks/raster.md - Raster/heatmap imagesmarks/hexgrid.md - Hexagonal gridsmarks/waffle.md - Waffle chartsmarks/delaunay.md - Voronoi and Delaunaymarks/bollinger.md - Bollinger bandsmarks/difference.md - Difference chartsmarks/tree.md - Hierarchical treesmarks/auto.md - Automatic mark selectionmarks/linear-regression.md - Trend linesmarks/crosshair.md - Interactive crosshairsmarks/grid.md - Grid linestransforms/bin.md - Binning for histogramstransforms/group.md - Grouping categorical datatransforms/stack.md - Stacking for area/bar chartstransforms/dodge.md - Beeswarm plotstransforms/hexbin.md - Hexagonal binningtransforms/window.md - Moving averagestransforms/select.md - Selecting specific pointstransforms/normalize.md - Normalizing valuesfeatures/scales.md - Scale configurationfeatures/facets.md - Small multiplesfeatures/projections.md - Map projectionsfeatures/legends.md - Legend configurationfeatures/interactions.md - Interactive featuresfeatures/curves.md - Line interpolationfeatures/markers.md - Line markersfeatures/shorthand.md - Concise syntaxfeatures/intervals.md - Time intervalsPlot.plot({
y: {grid: true},
marks: [Plot.line(data, {x: "date", y: "value"})]
})
Plot.plot({
color: {legend: true},
marks: [Plot.dot(data, {x: "x", y: "y", fill: "category"})]
})
Plot.plot({
facet: {data, x: "region"},
marks: [Plot.dot(data, {x: "income", y: "lifeExpectancy"})]
})
Plot.plot({
marks: [
Plot.dot(data, {x: "x", y: "y", tip: true})
]
})
Plot.plot({
marks: [
Plot.areaY(data, {x: "date", y: "value", fill: "category"})
]
})
import * as Plot from "@observablehq/plot";
import { useRef, useEffect } from "react";
function Chart({ data }) {
const ref = useRef();
useEffect(() => {
const plot = Plot.plot({
marks: [Plot.dot(data, {x: "x", y: "y"})]
});
ref.current.append(plot);
return () => plot.remove();
}, [data]);
return <div ref={ref} />;
}
const plot = Plot.plot({
marks: [Plot.dot(data, {x: "x", y: "y"})]
});
document.body.append(plot);
npx claudepluginhub maragudk/fabrik --plugin fabrikPython interactive visualization library for creating web-embeddable charts with hover, zoom, and pan. Includes Plotly Express and Graph Objects APIs.
Creates interactive, web-embeddable charts with 40+ chart types, hover info, zoom, and pan. Best for dashboards, exploratory analysis, and presentations.
Generates charts like bar, line, pie, scatter, heatmaps from data using Matplotlib. Analyzes structure, customizes styles, adds interactivity, exports to PNG, SVG, HTML.