Agent skill

d3js-visualization

Professional data visualization creation using D3.js with support for interactive charts, custom visualizations, animations, and responsive design. Use for: (1) Creating custom interactive charts, (2) Building dashboards, (3) Network/graph visualizations, (4) Geographic data mapping, (5) Time series analysis, (6) Real-time data visualization, (7) Complex multi-dimensional data displays

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SKILL.md

D3.js Data Visualization Skill

What is D3.js

D3.js (Data-Driven Documents) is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. It uses HTML, SVG, and CSS standards to bind data to the DOM and apply data-driven transformations.

When to Use D3.js

Choose D3.js when you need:

  • Custom, unique visualizations not available in chart libraries
  • Fine-grained control over every visual element
  • Complex interactions and animations
  • Data-driven DOM manipulation beyond just charts
  • Performance with large datasets (when using Canvas)
  • Web standards-based visualizations

Consider alternatives when:

  • Simple standard charts are sufficient (use Chart.js, Plotly)
  • Quick prototyping is priority (use Observable, Vega-Lite)
  • Static charts for print/reports (use matplotlib, ggplot2)
  • 3D visualizations (use Three.js, WebGL libraries)

D3.js vs Other Libraries

Library Best For Learning Curve Customization
D3.js Custom visualizations Steep Complete
Chart.js Standard charts Easy Limited
Plotly Scientific plots Medium Good
Highcharts Business dashboards Easy Good
Three.js 3D graphics Steep Complete

Core Workflow

1. Project Setup

Option 1: CDN (Quick Start)

html
<!DOCTYPE html>
<html>
<head>
  <meta charset="utf-8">
  <title>D3 Visualization</title>
  <style>
    body { margin: 0; font-family: sans-serif; }
    svg { display: block; }
  </style>
</head>
<body>
  <div id="chart"></div>
  <script src="https://d3js.org/d3.v7.min.js"></script>
  <script>
    // Your code here
  </script>
</body>
</html>

Option 2: NPM (Production)

bash
npm install d3
javascript
// Import all of D3
import * as d3 from "d3";

// Or import specific modules
import { select, selectAll } from "d3-selection";
import { scaleLinear, scaleTime } from "d3-scale";

2. Create Basic Chart

javascript
// Set up dimensions and margins
const margin = {top: 20, right: 30, bottom: 40, left: 50};
const width = 800 - margin.left - margin.right;
const height = 400 - margin.top - margin.bottom;

// Create SVG
const svg = d3.select("#chart")
  .append("svg")
  .attr("width", width + margin.left + margin.right)
  .attr("height", height + margin.top + margin.bottom)
  .append("g")
  .attr("transform", `translate(${margin.left},${margin.top})`);

// Load and process data
d3.csv("data.csv", d => ({
  date: new Date(d.date),
  value: +d.value
})).then(data => {

  // Create scales
  const xScale = d3.scaleTime()
    .domain(d3.extent(data, d => d.date))
    .range([0, width]);

  const yScale = d3.scaleLinear()
    .domain([0, d3.max(data, d => d.value)])
    .nice()
    .range([height, 0]);

  // Create and append axes
  svg.append("g")
    .attr("transform", `translate(0,${height})`)
    .call(d3.axisBottom(xScale));

  svg.append("g")
    .call(d3.axisLeft(yScale));

  // Create line generator
  const line = d3.line()
    .x(d => xScale(d.date))
    .y(d => yScale(d.value))
    .curve(d3.curveMonotoneX);

  // Draw line
  svg.append("path")
    .datum(data)
    .attr("d", line)
    .attr("fill", "none")
    .attr("stroke", "steelblue")
    .attr("stroke-width", 2);
});

3. Add Interactivity

Tooltips:

javascript
const tooltip = d3.select("body")
  .append("div")
  .attr("class", "tooltip")
  .style("position", "absolute")
  .style("visibility", "hidden")
  .style("background", "white")
  .style("border", "1px solid #ddd")
  .style("padding", "10px")
  .style("border-radius", "4px");

circles
  .on("mouseover", function(event, d) {
    tooltip
      .style("visibility", "visible")
      .html(`<strong>${d.name}</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() {
    tooltip.style("visibility", "hidden");
  });

Transitions:

javascript
circles
  .transition()
  .duration(300)
  .ease(d3.easeCubicOut)
  .attr("r", 8);

4. Implement Responsive Design

javascript
function createChart() {
  const container = d3.select("#chart");
  const containerWidth = container.node().getBoundingClientRect().width;

  const margin = {top: 20, right: 30, bottom: 40, left: 50};
  const width = containerWidth - margin.left - margin.right;
  const height = Math.min(width * 0.6, 500);

  container.selectAll("*").remove(); // Clear previous

  // Create SVG...
}

// Initial render
createChart();

// Re-render on resize with debouncing
let resizeTimer;
window.addEventListener("resize", () => {
  clearTimeout(resizeTimer);
  resizeTimer = setTimeout(createChart, 250);
});

Key Principles

Data Binding

  • Use .data() to bind data to DOM elements
  • Handle enter, update, and exit selections
  • Use key functions for consistent element-to-data matching
  • Modern syntax: use .join() for cleaner code

Scales

  • Map data values (domain) to visual values (range)
  • Use appropriate scale types (linear, time, band, ordinal)
  • Apply .nice() to scales for rounded axis values
  • Invert y-scale range for bottom-up coordinates: [height, 0]

SVG Coordinate System

  • Origin (0,0) is at top-left corner
  • Y increases downward (opposite of Cartesian)
  • Use margin convention for proper spacing
  • Group related elements with <g> tags

Performance

  • Use SVG for <1,000 elements
  • Use Canvas for >1,000 elements
  • Aggregate or sample large datasets
  • Debounce resize handlers

Chart Selection Guide

Time series data? → Line chart or area chart

Comparing categories? → Bar chart (vertical or horizontal)

Showing relationships? → Scatter plot or bubble chart

Part-to-whole? → Donut chart or stacked bar (limit to 5-7 categories)

Network data? → Force-directed graph

Distribution? → Histogram or box plot

See references/chart-types.md for detailed chart selection criteria and best practices.

Common Patterns

Quick Data Loading

javascript
// Load CSV with type conversion
d3.csv("data.csv", d => ({
  date: new Date(d.date),
  value: +d.value,
  category: d.category
})).then(data => {
  createChart(data);
});

Quick Tooltip

javascript
selection
  .on("mouseover", (event, d) => {
    tooltip.style("visibility", "visible").html(`Value: ${d.value}`);
  })
  .on("mousemove", (event) => {
    tooltip.style("top", event.pageY + "px").style("left", event.pageX + "px");
  })
  .on("mouseout", () => tooltip.style("visibility", "hidden"));

Quick Responsive SVG

javascript
svg
  .attr("viewBox", `0 0 ${width} ${height}`)
  .attr("preserveAspectRatio", "xMidYMid meet")
  .style("width", "100%")
  .style("height", "auto");

Quality Standards

Visual Quality

  • Use appropriate chart type for data
  • Apply consistent color schemes
  • Include clear axis labels and legends
  • Provide proper spacing with margin convention
  • Use appropriate scale types and ranges

Interaction Quality

  • Add meaningful tooltips
  • Use smooth transitions (300-500ms duration)
  • Provide hover feedback
  • Enable keyboard navigation for accessibility
  • Implement zoom/pan for detailed exploration

Code Quality

  • Use key functions in data joins
  • Handle enter, update, and exit properly
  • Clean up previous renders before updates
  • Use reusable chart pattern for modularity
  • Debounce expensive operations

Accessibility

  • Add ARIA labels and descriptions
  • Provide keyboard navigation
  • Use colorblind-safe palettes
  • Include text alternatives for screen readers
  • Ensure sufficient color contrast

Helper Resources

Available Scripts

  • data-helpers.js: Data loading, parsing, and transformation utilities
  • chart-templates.js: Reusable chart templates for common visualizations

See scripts/ directory for implementations.

Working Examples

  • line-chart.html: Time series visualization with tooltips
  • bar-chart.html: Grouped and stacked bar charts
  • network-graph.html: Force-directed network visualization

See examples/ directory for complete implementations.

Detailed References

  • D3 Fundamentals: SVG basics, data binding, selections, transitions, events → references/d3-fundamentals.md

  • Scales and Axes: All scale types, axis customization, color palettes → references/scales-and-axes.md

  • Paths and Shapes: Line/area generators, arcs, force simulations → references/paths-and-shapes.md

  • Data Transformation: Loading, parsing, grouping, aggregation, date handling → references/data-transformation.md

  • Chart Types: Detailed guidance on when to use each chart type → references/chart-types.md

  • Advanced Patterns: Reusable charts, performance optimization, responsive design → references/advanced-patterns.md

  • Common Pitfalls: Frequent mistakes and their solutions → references/common-pitfalls.md

  • Integration Patterns: Using D3 with React, Vue, Angular, Svelte → references/integration-patterns.md

Troubleshooting

Chart not appearing?

  • Check browser console for errors
  • Verify data loaded correctly
  • Ensure SVG has width and height
  • Check scale domains and ranges

Elements in wrong position?

  • Verify scale domain matches data range
  • Check if y-scale range is inverted: [height, 0]
  • Confirm margin transform applied to <g> element
  • Check SVG coordinate system (top-left origin)

Transitions not working?

  • Ensure duration is reasonable (300-500ms)
  • Check if transition applied to selection, not data
  • Verify easing function is valid
  • Confirm elements exist before transitioning

Poor performance?

  • Reduce number of DOM elements (use Canvas if >1,000)
  • Aggregate or sample data
  • Debounce resize handlers
  • Minimize redraws

External Resources

Official Documentation

Learning Resources

Color Tools

Inspiration

This skill provides comprehensive coverage of D3.js for creating professional, interactive data visualizations. Use the core workflow as a starting point, refer to the detailed references for specific topics, and customize the examples for your needs.

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