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)
    .
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