d3-viz
A guide for building bespoke, interactive data visualizations using D3.js across JavaScript frameworks.
Install
mkdir -p .claude/skills/d3-viz && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1436" && unzip -o skill.zip -d .claude/skills/d3-viz && rm skill.zipInstalls to .claude/skills/d3-viz
Activation
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Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.Key capabilities
- →Binds arbitrary data to DOM elements
- →Executes data-driven DOM transformations
- →Implements custom geometric and force-directed layouts
- →Generates interactive SVG pan and zoom behaviors
- →Constructs choreographed animation sequences
How it works
Uses a declarative selection mechanism to bind data to DOM nodes, applying transformation functions to synchronize element attributes with data states.
Inputs & outputs
When to use d3-viz
- →Building custom SVG-based charts
- →Creating force-directed graph diagrams
- →Implementing complex pan and zoom interactions
- →Designing custom geographic map projections
About this skill
D3.js Visualisation
Overview
This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js. D3.js (Data-Driven Documents) excels at binding data to DOM elements and applying data-driven transformations to create custom, publication-quality visualisations with precise control over every visual element. The techniques work across any JavaScript environment, including vanilla JavaScript, React, Vue, Svelte, and other frameworks.
When to use d3.js
Use d3.js for:
- Custom visualisations requiring unique visual encodings or layouts
- Interactive explorations with complex pan, zoom, or brush behaviours
- Network/graph visualisations (force-directed layouts, tree diagrams, hierarchies, chord diagrams)
- Geographic visualisations with custom projections
- Visualisations requiring smooth, choreographed transitions
- Publication-quality graphics with fine-grained styling control
- Novel chart types not available in standard libraries
Consider alternatives for:
- 3D visualisations - use Three.js instead
Core workflow
1. Set up d3.js
Import d3 at the top of your script:
import * as d3 from 'd3';
Or use the CDN version (7.x):
<script src="https://d3js.org/d3.v7.min.js"></script>
All modules (scales, axes, shapes, transitions, etc.) are accessible through the d3 namespace.
2. Choose the integration pattern
Pattern A: Direct DOM manipulation (recommended for most cases) Use d3 to select DOM elements and manipulate them imperatively. This works in any JavaScript environment:
function drawChart(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart'); // Select by ID, class, or DOM element
// Clear previous content
svg.selectAll("*").remove();
// Set up dimensions
const width = 800;
const height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
// Create scales, axes, and draw visualisation
// ... d3 code here ...
}
// Call when data changes
drawChart(myData);
Pattern B: Declarative rendering (for frameworks with templating) Use d3 for data calculations (scales, layouts) but render elements via your framework:
function getChartElements(data) {
const xScale = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([0, 400]);
return data.map((d, i) => ({
x: 50,
y: i * 30,
width: xScale(d.value),
height: 25
}));
}
// In React: {getChartElements(data).map((d, i) => <rect key={i} {...d} fill="steelblue" />)}
// In Vue: v-for directive over the returned array
// In vanilla JS: Create elements manually from the returned data
Use Pattern A for complex visualisations with transitions, interactions, or when leveraging d3's full capabilities. Use Pattern B for simpler visualisations or when your framework prefers declarative rendering.
3. Structure the visualisation code
Follow this standard structure in your drawing function:
function drawVisualization(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart'); // Or pass a selector/element
svg.selectAll("*").remove(); // Clear previous render
// 1. Define dimensions
const width = 800;
const height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
const innerWidth = width - margin.left - margin.right;
const innerHeight = height - margin.top - margin.bottom;
// 2. Create main group with margins
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
// 3. Create scales
const xScale = d3.scaleLinear()
.domain([0, d3.max(data, d => d.x)])
.range([0, innerWidth]);
const yScale = d3.scaleLinear()
.domain([0, d3.max(data, d => d.y)])
.range([innerHeight, 0]); // Note: inverted for SVG coordinates
// 4. Create and append axes
const xAxis = d3.axisBottom(xScale);
const yAxis = d3.axisLeft(yScale);
g.append("g")
.attr("transform", `translate(0,${innerHeight})`)
.call(xAxis);
g.append("g")
.call(yAxis);
// 5. Bind data and create visual elements
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", 5)
.attr("fill", "steelblue");
}
// Call when data changes
drawVisualization(myData);
4. Implement responsive sizing
Make visualisations responsive to container size:
function setupResponsiveChart(containerId, data) {
const container = document.getElementById(containerId);
const svg = d3.select(`#${containerId}`).append('svg');
function updateChart() {
const { width, height } = container.getBoundingClientRect();
svg.attr('width', width).attr('height', height);
// Redraw visualisation with new dimensions
drawChart(data, svg, width, height);
}
// Update on initial load
updateChart();
// Update on window resize
window.addEventListener('resize', updateChart);
// Return cleanup function
return () => window.removeEventListener('resize', updateChart);
}
// Usage:
// const cleanup = setupResponsiveChart('chart-container', myData);
// cleanup(); // Call when component unmounts or element removed
Or use ResizeObserver for more direct container monitoring:
function setupResponsiveChartWithObserver(svgElement, data) {
const observer = new ResizeObserver(() => {
const { width, height } = svgElement.getBoundingClientRect();
d3.select(svgElement)
.attr('width', width)
.attr('height', height);
// Redraw visualisation
drawChart(data, d3.select(svgElement), width, height);
});
observer.observe(svgElement.parentElement);
return () => observer.disconnect();
}
Common visualisation patterns
Bar chart
function drawBarChart(data, svgElement) {
if (!data || data.length === 0) return;
const svg = d3.select(svgElement);
svg.selectAll("*").remove();
const width = 800;
const height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
const innerWidth = width - margin.left - margin.right;
const innerHeight = height - margin.top - margin.bottom;
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
const xScale = d3.scaleBand()
.domain(data.map(d => d.category))
.range([0, innerWidth])
.padding(0.1);
const yScale = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([innerHeight, 0]);
g.append("g")
.attr("transform", `translate(0,${innerHeight})`)
.call(d3.axisBottom(xScale));
g.append("g")
.call(d3.axisLeft(yScale));
g.selectAll("rect")
.data(data)
.join("rect")
.attr("x", d => xScale(d.category))
.attr("y", d => yScale(d.value))
.attr("width", xScale.bandwidth())
.attr("height", d => innerHeight - yScale(d.value))
.attr("fill", "steelblue");
}
// Usage:
// drawBarChart(myData, document.getElementById('chart'));
Line chart
const line = d3.line()
.x(d => xScale(d.date))
.y(d => yScale(d.value))
.curve(d3.curveMonotoneX); // Smooth curve
g.append("path")
.datum(data)
.attr("fill", "none")
.attr("stroke", "steelblue")
.attr("stroke-width", 2)
.attr("d", line);
Scatter plot
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", d => sizeScale(d.size)) // Optional: size encoding
.attr("fill", d => colourScale(d.category)) // Optional: colour encoding
.attr("opacity", 0.7);
Chord diagram
A chord diagram shows relationships between entities in a circular layout, with ribbons representing flows between them:
function drawChordDiagram(data) {
// data format: array of objects with source, target, and value
// Example: [{ source: 'A', target: 'B', value: 10 }, ...]
if (!data || data.length === 0) return;
const svg = d3.select('#chart');
svg.selectAll("*").remove();
const width = 600;
const height = 600;
const innerRadius = Math.min(width, height) * 0.3;
const outerRadius = innerRadius + 30;
// Create matrix from data
const nodes = Array.from(new Set(data.flatMap(d => [d.source, d.target])));
const matrix = Array.from({ length: nodes.length }, () => Array(nodes.length).fill(0));
data.forEach(d => {
const i = nodes.indexOf(d.source);
const j = nodes.indexOf(d.target);
matrix[i][j] += d.value;
matrix[j][i] += d.value;
});
// Create chord layout
const chord = d3.chord()
.padAngle(0.05)
.sortSubgroups(d3.descending);
const arc = d3.arc()
.innerRadius(innerRadius)
.outerRadius(outerRadius);
const ribbon = d3.ribbon()
.source(d => d.source)
.target(d => d.target);
const colourScale = d3.scaleOrdinal(d3.schemeCategory10)
.domain(nodes);
const g = svg.append("g")
.attr("transform", `translate(${width / 2},${height / 2})`);
const chords = chord(matrix);
// Draw ribbons
g.append("g")
.attr("fill-opacity", 0.67)
.selectAll("path")
.data(chords)
.join("path")
.attr("d", ribbon)
.attr("fill", d => colourScale(nodes[d.source.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.source.index])).darker());
// Draw groups (arcs)
const group = g.append("g")
.selectAll("g")
.data(chords.groups)
.join("g");
group.append("path")
.attr("d", arc)
.attr("fill", d => colourScale(nodes[d.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.index])).darker());
// Add labels
group.append("text")
.each(d => { d.angle = (d.startAngle + d.endAngle) / 2; })
.attr("dy", "0.31em")
.attr("transform", d => `rotate(${(d.angle * 180 / Math.PI) - 90})translate(${outerRadius + 30})${d.angle > Math.PI ? "rotate(180)" : ""}`)
.attr("text-anchor", d => d.angle > Math.PI ? "end" : null)
.te
---
*Content truncated.*
When not to use it
- →Rendering high-performance 3D visualisations
- →Building standard business charts where high-level libraries suffice
Prerequisites
Limitations
- →Steep learning curve for complex transitions
- →Manual handling required for responsive design scaling
- →Potential performance degradation with excessive DOM nodes
How it compares
Unlike standard charting libraries that offer pre-canned templates, this provides granular control over individual DOM elements for bespoke visual logic.
Compared to similar skills
d3-viz side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| d3-viz (this skill) | 3 | 6mo | No flags | Advanced |
| zustand | 113 | 2mo | No flags | Intermediate |
| accessibility-compliance | 45 | 2mo | No flags | Intermediate |
| react-modernization | 21 | 2mo | No flags | Advanced |
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Example prompts that trigger this skill in your AI assistant.
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