| name | d3-viz |
| description | 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. |
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');
svg.selectAll("*").remove();
const width = 800;
const height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
}
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
}));
}
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');
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.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]);
const xAxis = d3.axisBottom(xScale);
const yAxis = d3.axisLeft(yScale);
g.append("g")
.attr("transform", `translate(0,${innerHeight})`)
.call(xAxis);
g.append("g")
.call(yAxis);
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", 5)
.attr("fill", "steelblue");
}
drawVisualization(myData);
4. Implement responsive sizing
Make visualisations responsive to container size:
function setupResponsiveChart(containerId, data) {
const container = document.getElementById(containerId);
const svg = d3.select(`#${containerId}`).append('svg');
function updateChart() {
const { width, height } = container.getBoundingClientRect();
svg.attr('width', width).attr('height', height);
drawChart(data, svg, width, height);
}
updateChart();
window.addEventListener('resize', updateChart);
return () => window.removeEventListener('resize', updateChart);
}
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);
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,${innerHeight})`)
.call(d3.axisBottom(xScale));
g.append("g")
.call(d3.axisLeft(yScale));
g.selectAll("rect")
.data(data)
.join("rect")
.attr("x", d => xScale(d.category))
.attr("y", d => yScale(d.value))
.attr("width", xScale.bandwidth())
.attr("height", d => innerHeight - yScale(d.value))
.attr("fill", "steelblue");
}
Line chart
const line = d3.line()
.x(d => xScale(d.date))
.y(d => yScale(d.value))
.curve(d3.curveMonotoneX);
g.append("path")
.datum(data)
.attr("fill", "none")
.attr("stroke", "steelblue")
.attr("stroke-width", 2)
.attr("d", line);
Scatter plot
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", d => sizeScale(d.size))
.attr("fill", d => colourScale(d.category))
.attr("opacity", 0.7);
Chord diagram
A chord diagram shows relationships between entities in a circular layout, with ribbons representing flows between them:
function drawChordDiagram(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart');
svg.selectAll("*").remove();
const width = 600;
const height = 600;
const innerRadius = Math.min(width, height) * 0.3;
const outerRadius = innerRadius + 30;
const nodes = Array.from(new Set(data.flatMap(d => [d.source, d.target])));
const matrix = Array.from({ length: nodes.length }, () => Array(nodes.length).fill(0));
data.forEach(d => {
const i = nodes.indexOf(d.source);
const j = nodes.indexOf(d.target);
matrix[i][j] += d.value;
matrix[j][i] += d.value;
});
const chord = d3.chord()
.padAngle(0.05)
.sortSubgroups(d3.descending);
const arc = d3.arc()
.innerRadius(innerRadius)
.outerRadius(outerRadius);
const ribbon = d3.ribbon()
.source(d => d.source)
.target(d => d.target);
const colourScale = d3.scaleOrdinal(d3.schemeCategory10)
.domain(nodes);
const g = svg.append("g")
.attr("transform", `translate(${width / 2},${height / 2})`);
const chords = chord(matrix);
g.append("g")
.attr("fill-opacity", 0.67)
.selectAll("path")
.data(chords)
.join("path")
.attr("d", ribbon)
.attr("fill", d => colourScale(nodes[d.source.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.source.index])).darker());
const group = g.append("g")
.selectAll("g")
.data(chords.groups)
.join("g");
group.append("path")
.attr("d", arc)
.attr("fill", d => colourScale(nodes[d.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.index])).darker());
group.append("text")
.each(d => { d.angle = (d.startAngle + d.endAngle) / 2; })
.attr("dy", "0.31em")
.attr("transform", d => `rotate(${(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) {
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;
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})`);
const xScale = d3.scaleBand()
.domain(columns)
.range([0, innerWidth])
.padding(0.01);
const yScale = d3.scaleBand()
.domain(rows)
.range([0, innerHeight])
.padding(0.01);
const colourScale = d3.scaleSequential(d3.interpolateYlOrRd)
.domain([0, d3.max(data, d => d.value)]);
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));
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");
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");
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);
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},${height / 2})`);
g.selectAll("path")
.data(pie(data))
.join("path")
.attr("d", arc)
.attr("fill", (d, i) => colourScale(i))
.attr("stroke", "white")
.attr("stroke-width", 2);
Force-directed network
const simulation = d3.forceSimulation(nodes)
.force("link", d3.forceLink(links).id(d => d.id).distance(100))
.force("charge", d3.forceManyBody().strength(-300))
.force("center", d3.forceCenter(width / 2, height / 2));
const link = g.selectAll("line")
.data(links)
.join("line")
.attr("stroke", "#999")
.attr("stroke-width", 1);
const node = g.selectAll("circle")
.data(nodes)
.join("circle")
.attr("r", 8)
.attr("fill", "steelblue")
.call(d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended));
simulation.on("tick", () => {
link
.attr("x1", d => d.source.x)
.attr("y1", d => d.source.y)
.attr("x2", d => d.target.x)
.attr("y2", d => d.target.y);
node
.attr("cx", d => d.x)
.attr("cy", d => d.y);
});
function dragstarted(event) {
if (!event.active) simulation.alphaTarget(0.3).restart();
event.subject.fx = event.subject.x;
event.subject.fy = event.subject.y;
}
function dragged(event) {
event.subject.fx = event.x;
event.subject.fy = event.y;
}
function dragended(event) {
if (!event.active) simulation.alphaTarget(0);
event.subject.fx = null;
event.subject.fy = null;
}
Adding interactivity
Tooltips
const tooltip = d3.select("body").append("div")
.attr("class", "tooltip")
.style("position", "absolute")
.style("visibility", "hidden")
.style("background-color", "white")
.style("border", "1px solid #ddd")
.style("padding", "10px")
.style("border-radius", "4px")
.style("pointer-events", "none");
circles
.on("mouseover", function(event, d) {
d3.select(this).attr("opacity", 1);
tooltip
.style("visibility", "visible")
.html(`<strong>${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) {
console.log("Clicked:", d);
d3.selectAll("circle").attr("fill", "steelblue");
d3.select(this).attr("fill", "orange");
});
Transitions and animations
Add smooth transitions to visual changes:
circles
.transition()
.duration(750)
.attr("r", 10);
circles
.transition()
.duration(500)
.attr("fill", "orange")
.transition()
.duration(500)
.attr("r", 15);
circles
.transition()
.delay((d, i) => i * 50)
.duration(500)
.attr("cy", d => yScale(d.value));
circles
.transition()
.duration(1000)
.ease(d3.easeBounceOut)
.attr("r", 10);
Scales reference
Quantitative scales
const xScale = d3.scaleLinear()
.domain([0, 100])
.range([0, 500]);
const logScale = d3.scaleLog()
.domain([1, 1000])
.range([0, 500]);
const powScale = d3.scalePow()
.exponent(2)
.domain([0, 100])
.range([0, 500]);
const timeScale = d3.scaleTime()
.domain([new Date(2020, 0, 1), new Date(2024, 0, 1)])
.range([0, 500]);
Ordinal scales
const bandScale = d3.scaleBand()
.domain(['A', 'B', 'C', 'D'])
.range([0, 400])
.padding(0.1);
const pointScale = d3.scalePoint()
.domain(['A', 'B', 'C', 'D'])
.range([0, 400]);
const colourScale = d3.scaleOrdinal(d3.schemeCategory10);
Sequential scales
const colourScale = d3.scaleSequential(d3.interpolateBlues)
.domain([0, 100]);
const divScale = d3.scaleDiverging(d3.interpolateRdBu)
.domain([-10, 0, 10]);
Best practices
Data preparation
Always validate and prepare data before visualisation:
const cleanData = data.filter(d => d.value != null && !isNaN(d.value));
const sortedData = [...data].sort((a, b) => b.value - a.value);
const parsedData = data.map(d => ({
...d,
date: d3.timeParse("%Y-%m-%d")(d.date)
}));
Performance optimisation
For large datasets (>1000 elements):
Accessibility
Make visualisations accessible:
svg.attr("role", "img")
.attr("aria-label", "Bar chart showing quarterly revenue");
svg.append("title").text("Quarterly Revenue 2024");
svg.append("desc").text("Bar chart showing revenue growth across four quarters");
Styling
Use consistent, professional styling:
const colours = {
primary: '#4A90E2',
secondary: '#7B68EE',
background: '#F5F7FA',
text: '#333333',
gridLines: '#E0E0E0'
};
svg.selectAll("text")
.style("font-family", "Inter, sans-serif")
.style("font-size", "12px");
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 examples
scale-reference.md - Complete guide to d3 scales with examples
colour-schemes.md - D3 colour schemes and palette recommendations
assets/
Contains boilerplate templates:
chart-template.js - Starter template for basic chart
interactive-template.js - Template with tooltips, zoom, and interactions
sample-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.