d3js-visualization

majiayu000

Updated Yesterday

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Metadesigndata

About

This skill creates custom, interactive D3.js visualizations for complex or unique data display needs. It's ideal when you require fine-grained control over charts, graphs, maps, or real-time dashboards beyond standard chart libraries. Use it to build responsive, animated visualizations with custom interactions and data-driven DOM manipulation.

Quick Install

Claude Code

Recommended

Plugin CommandRecommended

/plugin add https://github.com/majiayu000/claude-skill-registry

Git CloneAlternative

git clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/d3js-visualization

Copy and paste this command in Claude Code to install this skill

Documentation

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)

<!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)

npm install d3

// 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

// 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:

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:

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

4. Implement Responsive Design

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

// 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

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

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

D3.js API Reference: https://d3js.org/
Observable Examples: https://observablehq.com/@d3

Learning Resources

"Interactive Data Visualization for the Web" by Scott Murray
D3 Graph Gallery: https://d3-graph-gallery.com/
Amelia Wattenberger's D3 Tutorial: https://wattenberger.com/blog/d3

Color Tools

ColorBrewer: https://colorbrewer2.org/
D3 Color Schemes: https://d3js.org/d3-scale-chromatic

Inspiration

Observable Trending: https://observablehq.com/trending
Reddit r/dataisbeautiful: https://reddit.com/r/dataisbeautiful

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.

GitHub Repository

majiayu000/claude-skill-registry

Path: skills/d3js-visualization

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