
D3.js Visualisation
FreeCreate interactive and custom data visualisations with D3.js.
Free · Opens the source repo
What D3.js Visualisation does
The D3.js Visualisation skill provides comprehensive guidance for developers looking to create interactive and sophisticated data visualisations using the D3.js library. D3.js is particularly powerful for binding data to DOM elements and applying data-driven transformations, allowing for the creation of custom visualisations that can be tailored to specific needs. This skill is suitable for various JavaScript environments, including React, Vue, Svelte, and vanilla JavaScript, making it versatile for different project requirements.
With this skill, users can implement a wide range of visualisation types, from standard charts to complex network diagrams and geographic visualisations. D3.js excels in scenarios where fine-grained control over visual elements, transitions, and interactions is necessary. Whether you need to create bespoke visualisations that go beyond the capabilities of standard charting libraries or require publication-quality graphics with precise styling, this skill offers the foundational knowledge and patterns needed to succeed.
The skill includes detailed instructions on setting up D3.js, choosing the right integration pattern, and structuring visualisation code effectively. It also covers common visualisation patterns such as bar charts, line charts, scatter plots, and chord diagrams, providing users with practical examples that can be adapted to their specific data sets. Additionally, the skill emphasizes the importance of responsive design, ensuring that visualisations can adjust to different container sizes, enhancing user experience across devices.
Overall, this skill is ideal for developers and designers who need to create custom, interactive data visualisations that require a high level of customization and control. It empowers users to leverage D3.js effectively, enabling them to produce engaging and informative visual representations of data.
When to use it
Use this skill when you need to create custom charts, graphs, or any complex SVG-based visualisation that requires detailed control over the visual output.
When not to use it
Avoid this skill for simple visualisations or when 3D graphics are required, as D3.js is not designed for 3D visualisations.
What you can build with it
Custom Data Dashboard
Create an interactive dashboard with various charts and graphs to visualize real-time data updates.
Network Analysis
Visualize complex relationships between data points using force-directed graphs or chord diagrams.
Geographic Data Representation
Build custom maps with data overlays to represent geographical data in a meaningful way.
How to install D3.js Visualisation
View source1. Install with the skills CLI
npx skills add calesthio/openmontage/d3-viz --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by calesthioD3.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)
.text((d, i) => nodes[i])
.style("font-size", "12px");
}
Heatmap
A heatmap uses colour to encode values in a two-dimensional grid, useful for showing patterns across categories:
function drawHeatmap(data) {
// data format: array of objects with row, column, and value
// Example: [{ row: 'A', column: 'X', value: 10 }, ...]
if (!data || data.length === 0) return;
const svg = d3.select('#chart');
svg.selectAll("*").remove();
const width = 800;
const height = 600;
const margin = { top: 100, right: 30, bottom: 30, left: 100 };
const innerWidth = width - margin.left - margin.right;
const innerHeight = height - margin.top - margin.bottom;
// Get unique rows and columns
const rows = Array.from(new Set(data.map(d => d.row)));
const columns = Array.from(new Set(data.map(d => d.column)));
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
// Create scales
const xScale = d3.scaleBand()
.domain(columns)
.range([0, innerWidth])
.padding(0.01);
const yScale = d3.scaleBand()
.domain(rows)
.range([0, innerHeight])
.padding(0.01);
// Colour scale for values
const colourScale = d3.scaleSequential(d3.interpolateYlOrRd)
.domain([0, d3.max(data, d => d.value)]);
// Draw rectangles
g.selectAll("rect")
.data(data)
.join("rect")
.attr("x", d => xScale(d.column))
.attr("y", d => yScale(d.row))
.attr("width", xScale.bandwidth())
.attr("height", yScale.bandwidth())
.attr("fill", d => colourScale(d.value));
// Add x-axis labels
svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`)
.selectAll("text")
.data(columns)
.join("text")
.attr("x", d => xScale(d) + xScale.bandwidth() / 2)
.attr("y", -10)
.attr("text-anchor", "middle")
.text(d => d)
.style("font-size", "12px");
// Add y-axis labels
svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`)
.selectAll("text")
.data(rows)
.join("text")
.attr("x", -10)
.attr("y", d => yScale(d) + yScale.bandwidth() / 2)
.attr("dy", "0.35em")
.attr("text-anchor", "end")
.text(d => d)
.style("font-size", "12px");
// Add colour legend
const legendWidth = 20;
const legendHeight = 200;
const legend = svg.append("g")
.attr("transform", `translate(${width - 60},${margin.top})`);
const legendScale = d3.scaleLinear()
.domain(colourScale.domain())
.range([legendHeight, 0]);
const legendAxis = d3.axisRight(legendScale)
.ticks(5);
// Draw colour gradient in legend
for (let i = 0; i < legendHeight; i++) {
legend.append("rect")
.attr("y", i)
.attr("width", legendWidth)
.attr("height", 1)
.attr("fill", colourScale(legendScale.invert(i)));
}
legend.append("g")
.attr("transform", `translate(${legendWidth},0)`)
.call(legendAxis);
}
Pie chart
const pie = d3.pie()
.value(d => d.value)
.sort(null);
const arc = d3.arc()
.innerRadius(0)
.outerRadius(Math.min(width, height) / 2 - 20);
const colourScale = d3.scaleOrdinal(d3.schemeCategory10);
const g = svg.append("g")
.attr("transform", `translate(${width / 2},${height / 2})`);
g.selectAll("path")
.data(pie(data))
.join("path")
.attr("d", arc)
.attr("fill", (d, i) => colourScale(i))
.attr("stroke", "white")
.attr("stroke-width", 2);
Force-directed network
const simulation = d3.forceSimulation(nodes)
.force("link", d3.forceLink(links).id(d => d.id).distance(100))
.force("charge", d3.forceManyBody().strength(-300))
.force("center", d3.forceCenter(width / 2, height / 2));
const link = g.selectAll("line")
.data(links)
.join("line")
.attr("stroke", "#999")
.attr("stroke-width", 1);
const node = g.selectAll("circle")
.data(nodes)
.join("circle")
.attr("r", 8)
.attr("fill", "steelblue")
.call(d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended));
simulation.on("tick", () => {
link
.attr("x1", d => d.source.x)
.attr("y1", d => d.source.y)
.attr("x2", d => d.target.x)
.attr("y2", d => d.target.y);
node
.attr("cx", d => d.x)
.attr("cy", d => d.y);
});
function dragstarted(event) {
if (!event.active) simulation.alphaTarget(0.3).restart();
event.subject.fx = event.subject.x;
event.subject.fy = event.subject.y;
}
function dragged(event) {
event.subject.fx = event.x;
event.subject.fy = event.y;
}
function dragended(event) {
if (!event.active) simulation.alphaTarget(0);
event.subject.fx = null;
event.subject.fy = null;
}
Adding interactivity
Tooltips
// Create tooltip div (outside SVG)
const tooltip = d3.select("body").append("div")
.attr("class", "tooltip")
.style("position", "absolute")
.style("visibility", "hidden")
.style("background-color", "white")
.style("border", "1px solid #ddd")
.style("padding", "10px")
.style("border-radius", "4px")
.style("pointer-events", "none");
// Add to elements
circles
.on("mouseover", function(event, d) {
d3.select(this).attr("opacity", 1);
tooltip
.style("visibility", "visible")
.html(`<strong>${d.label}</strong><br/>Value: ${d.value}`);
})
.on("mousemove", function(event) {
tooltip
.style("top", (event.pageY - 10) + "px")
.style("left", (event.pageX + 10) + "px");
})
.on("mouseout", function() {
d3.select(this).attr("opacity", 0.7);
tooltip.style("visibility", "hidden");
});
Zoom and pan
const zoom = d3.zoom()
.scaleExtent([0.5, 10])
.on("zoom", (event) => {
g.attr("transform", event.transform);
});
svg.call(zoom);
Click interactions
circles
.on("click", function(event, d) {
// Handle click (dispatch event, update app state, etc.)
console.log("Clicked:", d);
// Visual feedback
d3.selectAll("circle").attr("fill", "steelblue");
d3.select(this).attr("fill", "orange");
// Optional: dispatch custom event for your framework/app to listen to
// window.dispatchEvent(new CustomEvent('chartClick', { detail: d }));
});
Transitions and animations
Add smooth transitions to visual changes:
// Basic transition
circles
.transition()
.duration(750)
.attr("r", 10);
// Chained transitions
circles
.transition()
.duration(500)
.attr("fill", "orange")
.transition()
.duration(500)
.attr("r", 15);
// Staggered transitions
circles
.transition()
.delay((d, i) => i * 50)
.duration(500)
.attr("cy", d => yScale(d.value));
// Custom easing
circles
.transition()
.duration(1000)
.ease(d3.easeBounceOut)
.attr("r", 10);
Scales reference
Quantitative scales
// Linear scale
const xScale = d3.scaleLinear()
.domain([0, 100])
.range([0, 500]);
// Log scale (for exponential data)
const logScale = d3.scaleLog()
.domain([1, 1000])
.range([0, 500]);
// Power scale
const powScale = d3.scalePow()
.exponent(2)
.domain([0, 100])
.range([0, 500]);
// Time scale
const timeScale = d3.scaleTime()
.domain([new Date(2020, 0, 1), new Date(2024, 0, 1)])
.range([0, 500]);
Ordinal scales
// Band scale (for bar charts)
const bandScale = d3.scaleBand()
.domain(['A', 'B', 'C', 'D'])
.range([0, 400])
.padding(0.1);
// Point scale (for line/scatter categories)
const pointScale = d3.scalePoint()
.domain(['A', 'B', 'C', 'D'])
.range([0, 400]);
// Ordinal scale (for colours)
const colourScale = d3.scaleOrdinal(d3.schemeCategory10);
Sequential scales
// Sequential colour scale
const colourScale = d3.scaleSequential(d3.interpolateBlues)
.domain([0, 100]);
// Diverging colour scale
const divScale = d3.scaleDiverging(d3.interpolateRdBu)
.domain([-10, 0, 10]);
Best practices
Data preparation
Always validate and prepare data before visualisation:
// Filter invalid values
const cleanData = data.filter(d => d.value != null && !isNaN(d.value));
// Sort data if order matters
const sortedData = [...data].sort((a, b) => b.value - a.value);
// Parse dates
const parsedData = data.map(d => ({
...d,
date: d3.timeParse("%Y-%m-%d")(d.date)
}));
Performance optimisation
For large datasets (>1000 elements):
// Use canvas instead of SVG for many elements
// Use quadtree for collision detection
// Simplify paths with d3.line().curve(d3.curveStep)
// Implement virtual scrolling for large lists
// Use requestAnimationFrame for custom animations
Accessibility
Make visualisations accessible:
// Add ARIA labels
svg.attr("role", "img")
.attr("aria-label", "Bar chart showing quarterly revenue");
// Add title and description
svg.append("title").text("Quarterly Revenue 2024");
svg.append("desc").text("Bar chart showing revenue growth across four quarters");
// Ensure sufficient colour contrast
// Provide keyboard navigation for interactive elements
// Include data table alternative
Styling
Use consistent, professional styling:
// Define colour palettes upfront
const colours = {
primary: '#4A90E2',
secondary: '#7B68EE',
background: '#F5F7FA',
text: '#333333',
gridLines: '#E0E0E0'
};
// Apply consistent typography
svg.selectAll("text")
.style("font-family", "Inter, sans-serif")
.style("font-size", "12px");
// Use subtle grid lines
g.selectAll(".tick line")
.attr("stroke", colours.gridLines)
.attr("stroke-dasharray", "2,2");
Common issues and solutions
Issue: Axes not appearing
- Ensure scales have valid domains (check for NaN values)
- Verify axis is appended to correct group
- Check transform translations are correct
Issue: Transitions not working
- Call
.transition()before attribute changes - Ensure elements have unique keys for proper data binding
- Check that useEffect dependencies include all changing data
Issue: Responsive sizing not working
- Use ResizeObserver or window resize listener
- Update dimensions in state to trigger re-render
- Ensure SVG has width/height attributes or viewBox
Issue: Performance problems
- Limit number of DOM elements (consider canvas for >1000 items)
- Debounce resize handlers
- Use
.join()instead of separate enter/update/exit selections - Avoid unnecessary re-renders by checking dependencies
Resources
references/
Contains detailed reference materials:
d3-patterns.md- Comprehensive collection of visualisation patterns and code examplesscale-reference.md- Complete guide to d3 scales with examplescolour-schemes.md- D3 colour schemes and palette recommendations
assets/
Contains boilerplate templates:
chart-template.js- Starter template for basic chartinteractive-template.js- Template with tooltips, zoom, and interactionssample-data.json- Example datasets for testing
These templates work with vanilla JavaScript, React, Vue, Svelte, or any other JavaScript environment. Adapt them as needed for your specific framework.
To use these resources, read the relevant files when detailed guidance is needed for specific visualisation types or patterns.
Frequently asked questions about D3.js Visualisation
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