정보
d3-viz 스킬은 d3.js를 사용하여 맞춤형 인터랙티브 데이터 시각화를 제작하는 방법에 대한 지침을 제공합니다. 표준 라이브러리로 구현하기 어려운 맞춤형 차트, 그래프, 다이어그램을 제작할 때 SVG 요소, 전환 효과, 상호작용을 세밀하게 제어해야 하는 경우에 사용하세요. 바닐라 자바스크립트나 React, Vue, Svelte 같은 프레임워크에서의 구현을 지원합니다.
빠른 설치
Claude Code
추천npx skills add chrisvoncsefalvay/claude-d3js-skill -a claude-code/plugin add https://github.com/chrisvoncsefalvay/claude-d3js-skillgit clone https://github.com/chrisvoncsefalvay/claude-d3js-skill.git ~/.claude/skills/d3-vizClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
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,${innerHeight})`)
.call(xAxis);
g.append("g")
.call(yAxis);
// 5. Bind data and create visual elements
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", 5)
.attr("fill", "steelblue");
}
// Call when data changes
drawVisualization(myData);
4. Implement responsive sizing
Make visualisations responsive to container size:
function setupResponsiveChart(containerId, data) {
const container = document.getElementById(containerId);
const svg = d3.select(`#${containerId}`).append('svg');
function updateChart() {
const { width, height } = container.getBoundingClientRect();
svg.attr('width', width).attr('height', height);
// 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()
.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");
}
// Usage:
// drawBarChart(myData, document.getElementById('chart'));
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.source);
const j = nodes.indexOf(d.target);
matrix[i][j] += d.value;
matrix[j][i] += d.value;
});
// Create chord layout
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},${height / 2})`);
const chords = chord(matrix);
// Draw ribbons
g.append("g")
.attr("fill-opacity", 0.67)
.selectAll("path")
.data(chords)
.join("path")
.attr("d", ribbon)
.attr("fill", d => colourScale(nodes[d.source.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.source.index])).darker());
// Draw groups (arcs)
const group = g.append("g")
.selectAll("g")
.data(chords.groups)
.join("g");
group.append("path")
.attr("d", arc)
.attr("fill", d => colourScale(nodes[d.index]))
.attr("stroke", d => d3.rgb(colourScale(nodes[d.index])).darker());
// Add labels
group.append("text")
.each(d => { d.angle = (d.startAngle + d.endAngle) / 2; })
.attr("dy", "0.31em")
.attr("transform", d => `rotate(${(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) {
// 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.column)));
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
// Create scales
const xScale = d3.scaleBand()
.domain(columns)
.range([0, innerWidth])
.padding(0.01);
const yScale = d3.scaleBand()
.domain(rows)
.range([0, innerHeight])
.padding(0.01);
// Colour scale for values
const colourScale = d3.scaleSequential(d3.interpolateYlOrRd)
.domain([0, d3.max(data, d => d.value)]);
// Draw rectangles
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));
// Add x-axis labels
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");
// Add y-axis labels
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");
// Add colour legend
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);
// Draw colour gradient in legend
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},${height / 2})`);
g.selectAll("path")
.data(pie(data))
.join("path")
.attr("d", arc)
.attr("fill", (d, i) => colourScale(i))
.attr("stroke", "white")
.attr("stroke-width", 2);
Force-directed network
const simulation = d3.forceSimulation(nodes)
.force("link", d3.forceLink(links).id(d => d.id).distance(100))
.force("charge", d3.forceManyBody().strength(-300))
.force("center", d3.forceCenter(width / 2, height / 2));
const link = g.selectAll("line")
.data(links)
.join("line")
.attr("stroke", "#999")
.attr("stroke-width", 1);
const node = g.selectAll("circle")
.data(nodes)
.join("circle")
.attr("r", 8)
.attr("fill", "steelblue")
.call(d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended));
simulation.on("tick", () => {
link
.attr("x1", d => d.source.x)
.attr("y1", d => d.source.y)
.attr("x2", d => d.target.x)
.attr("y2", d => d.target.y);
node
.attr("cx", d => d.x)
.attr("cy", d => d.y);
});
function dragstarted(event) {
if (!event.active) simulation.alphaTarget(0.3).restart();
event.subject.fx = event.subject.x;
event.subject.fy = event.subject.y;
}
function dragged(event) {
event.subject.fx = event.x;
event.subject.fy = event.y;
}
function dragended(event) {
if (!event.active) simulation.alphaTarget(0);
event.subject.fx = null;
event.subject.fy = null;
}
Adding interactivity
Tooltips
// Create tooltip div (outside SVG)
const tooltip = d3.select("body").append("div")
.attr("class", "tooltip")
.style("position", "absolute")
.style("visibility", "hidden")
.style("background-color", "white")
.style("border", "1px solid #ddd")
.style("padding", "10px")
.style("border-radius", "4px")
.style("pointer-events", "none");
// Add to elements
circles
.on("mouseover", function(event, d) {
d3.select(this).attr("opacity", 1);
tooltip
.style("visibility", "visible")
.html(`<strong>${d.label}</strong><br/>Value: ${d.value}`);
})
.on("mousemove", function(event) {
tooltip
.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) {
// 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 examplesscale-reference.md- Complete guide to d3 scales with examplescolour-schemes.md- D3 colour schemes and palette recommendations
assets/
Contains boilerplate templates:
chart-template.js- Starter template for basic chartinteractive-template.js- Template with tooltips, zoom, and interactionssample-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.
GitHub 저장소
자주 묻는 질문
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d3-viz은(는) chrisvoncsefalvay이(가) 만든 Claude Skill입니다. Skill은 Claude가 필요할 때 불러오는 지침과 리소스를 묶어 추가 프롬프트 없이 d3-viz 관련 작업을 수행할 수 있게 합니다.
d3-viz은(는) 어떻게 설치하나요?
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d3-viz은(는) 무료로 사용할 수 있나요?
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연관 스킬
이 스킬은 콘텐츠 콜렉션(Content Collections)을 위한 프로덕션 검증된 설정을 제공합니다. 콘텐츠 콜렉션은 Markdown/MDX 파일을 Zod 검증이 포함된 타입 안전한 데이터 콜렉션으로 변환해주는 TypeScript 최우선 도구입니다. 블로그, 문서 사이트 또는 콘텐츠 중심의 Vite + React 애플리케이션을 구축할 때 타입 안전성과 자동 콘텐츠 검증을 보장하기 위해 사용하세요. Vite 플러그인 구성과 MDX 컴파일부터 배포 최적화 및 스키마 검증에 이르기까지 모든 것을 다룹니다.
이 스킬은 개발자들이 Polymarket 예측 시장 플랫폼을 활용한 애플리케이션을 구축할 수 있도록 지원하며, 거래 및 시장 데이터를 위한 API 통합 기능을 포함합니다. 또한 WebSocket을 통한 실시간 데이터 스트리밍을 제공하여 실시간 거래와 시장 활동을 모니터링할 수 있습니다. 이를 통해 거래 전략을 구현하거나 실시간 시장 업데이트를 처리하는 도구를 생성하는 데 활용할 수 있습니다.
이 스킬은 개발자들이 명령어, 파일, LSP 작업 등 25개 이상의 이벤트 유형에 연결되는 OpenCode 플러그인을 만들 수 있도록 돕습니다. JavaScript/TypeScript 모듈을 위한 플러그인 구조, 이벤트 API 명세, 구현 패턴을 제공합니다. OpenCode AI 어시스턴트의 라이프사이클을 사용자 정의 이벤트 기반 로직으로 가로채거나, 모니터링하거나, 확장해야 할 때 사용하세요.
SGLang은 RadixAttention 프리픽스 캐싱을 활용하여 JSON, 정규식, 에이전트 워크플로우를 위한 고속 구조화 생성에 특화된 고성능 LLM 서빙 프레임워크입니다. 특히 반복되는 프리픽스가 있는 작업에서 상당히 빠른 추론 속도를 제공하여 복잡한 구조화 출력 및 다중 턴 대화에 이상적입니다. 제약 디코딩이 필요하거나 광범위한 프리픽스 공유가 있는 애플리케이션을 구축할 때는 vLLM과 같은 대안보다 SGLang을 선택하십시오.
