d3-viz

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'); // 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.)])
    .([, innerWidth]);

   yScale = d3.()
    .([, d3.(data,  d.)])
    .([innerHeight, ]); 

  
   xAxis = d3.(xScale);
   yAxis = d3.(yScale);

  g.()
    .(, )
    .(xAxis);

  g.()
    .(yAxis);

  
  g.()
    .(data)
    .()
    .(,  (d.))
    .(,  (d.))
    .(, )
    .(, );
}


(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()
    .([, d3.(data,  d.)])
    .([innerHeight, ]);

  g.()
    .(, )
    .(d3.(xScale));

  g.()
    .(d3.(yScale));

  g.()
    .(data)
    .()
    .(,  (d.))
    .(,  (d.))
    .(, xScale.())
    .(,  innerHeight - (d.))
    .(, );
}

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.);
     j = nodes.(d.);
    matrix[i][j] += d.;
    matrix[j][i] += d.;
  });

  
   chord = d3.()
    .()
    .(d3.);

   arc = d3.()
    .(innerRadius)
    .(outerRadius);

   ribbon = d3.()
    .( d.)
    .( d.);

   colourScale = d3.(d3.)
    .(nodes);

   g = svg.()
    .(, );

   chords = (matrix);

  
  g.()
    .(, )
    .()
    .(chords)
    .()
    .(, ribbon)
    .(,  (nodes[d..]))
    .(,  d3.((nodes[d..])).());

  
   group = g.()
    .()
    .(chords.)
    .();

  group.()
    .(, arc)
    .(,  (nodes[d.]))
    .(,  d3.((nodes[d.])).());

  
  group.()
    .( { d. = (d. + d.) / ; })
    .(, )
    .(,  )
    .(,  d. > . ?  : )
    .( nodes[i])
    .(, );
}

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.)));

   g = svg.()
    .(, );

  
   xScale = d3.()
    .(columns)
    .([, innerWidth])
    .();

   yScale = d3.()
    .(rows)
    .([, innerHeight])
    .();

  
   colourScale = d3.(d3.)
    .([, d3.(data,  d.)]);

  
  g.()
    .(data)
    .()
    .(,  (d.))
    .(,  (d.))
    .(, xScale.())
    .(, yScale.())
    .(,  (d.));

  
  svg.()
    .(, )
    .()
    .(columns)
    .()
    .(,  (d) + xScale.() / )
    .(, -)
    .(, )
    .( d)
    .(, );

  
  svg.()
    .(, )
    .()
    .(rows)
    .()
    .(, -)
    .(,  (d) + yScale.() / )
    .(, )
    .(, )
    .( d)
    .(, );

  
   legendWidth = ;
   legendHeight = ;
   legend = svg.()
    .(, );

   legendScale = d3.()
    .(colourScale.())
    .([legendHeight, ]);

   legendAxis = d3.(legendScale)
    .();

  
   ( i = ; i < legendHeight; i++) {
    legend.()
      .(, i)
      .(, legendWidth)
      .(, )
      .(, (legendScale.(i)));
  }

  legend.()
    .(, )
    .(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)
    .(, dragended));

simulation.(,  {
  link
    .(,  d..)
    .(,  d..)
    .(,  d..)
    .(,  d..);
  
  node
    .(,  d.)
    .(,  d.);
});

 () {
   (!event.) simulation.().();
  event.. = event..;
  event.. = event..;
}

 () {
  event.. = event.;
  event.. = event.;
}

 () {
   (!event.) simulation.();
  event.. = ;
  event.. = ;
}

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
      .(, (event. - ) + )
      .(, (event. + ) + );
  })
  .(, () {
    d3.().(, );
    tooltip.(, );
  });

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 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.