---
name: d3-viz-e9ce1b6b2a00
description: Create interactive data visualizations using D3.js. Use this when creating charts, graphs, network diagrams, geographic visualizations, or custom SVG-based data visualization.
allowed-tools: Read, Glob, Grep, Edit, Write
license: MIT
metadata:
  author: chrisvoncsefalvay
  version: "1.0"
---

# D3.js Visualization

D3.js를 사용한 인터랙티브 데이터 시각화 가이드입니다.

## When to Use D3.js

**적합한 경우:**
- 커스텀 차트 (표준 라이브러리에 없는)
- 인터랙티브 탐색 (pan, zoom, brush)
- 네트워크/그래프 시각화
- 지리 시각화 (커스텀 projection)
- 애니메이션 transition
- 출판 품질 그래픽

**대안 고려:**
- 3D 시각화 → Three.js
- 간단한 차트 → Chart.js, Recharts

## Setup

```javascript
// npm
import * as d3 from 'd3';

// CDN
<script src="https://d3js.org/d3.v7.min.js"></script>
```

## Core Workflow

```javascript
function drawVisualization(data) {
  if (!data || data.length === 0) return;

  const svg = d3.select('#chart');
  svg.selectAll("*").remove(); // Clear previous

  // 1. 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. Main group with margins
  const g = svg.append("g")
    .attr("transform", `translate(${margin.left},${margin.top})`);

  // 3. 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]);

  // 4. Axes
  g.append("g")
    .attr("transform", `translate(0,${innerHeight})`)
    .call(d3.axisBottom(xScale));

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

  // 5. Data binding
  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");
}
```

## Common Patterns

### Bar Chart
```javascript
const xScale = d3.scaleBand()
  .domain(data.map(d => d.category))
  .range([0, innerWidth])
  .padding(0.1);

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");
```

### Line Chart
```javascript
const line = d3.line()
  .x(d => xScale(d.date))
  .y(d => yScale(d.value))
  .curve(d3.curveMonotoneX);

g.append("path")
  .datum(data)
  .attr("fill", "none")
  .attr("stroke", "steelblue")
  .attr("stroke-width", 2)
  .attr("d", line);
```

### Pie Chart
```javascript
const pie = d3.pie().value(d => d.value);
const arc = d3.arc()
  .innerRadius(0)
  .outerRadius(Math.min(width, height) / 2 - 20);

g.selectAll("path")
  .data(pie(data))
  .join("path")
  .attr("d", arc)
  .attr("fill", (d, i) => d3.schemeCategory10[i]);
```

## Interactivity

### Tooltips
```javascript
const tooltip = d3.select("body").append("div")
  .attr("class", "tooltip")
  .style("visibility", "hidden");

circles
  .on("mouseover", (event, d) => {
    tooltip.style("visibility", "visible")
      .html(`Value: ${d.value}`);
  })
  .on("mousemove", (event) => {
    tooltip
      .style("top", (event.pageY - 10) + "px")
      .style("left", (event.pageX + 10) + "px");
  })
  .on("mouseout", () => {
    tooltip.style("visibility", "hidden");
  });
```

### Zoom & Pan
```javascript
const zoom = d3.zoom()
  .scaleExtent([0.5, 10])
  .on("zoom", (event) => {
    g.attr("transform", event.transform);
  });

svg.call(zoom);
```

## Transitions

```javascript
// Basic
circles.transition()
  .duration(750)
  .attr("r", 10);

// Staggered
circles.transition()
  .delay((d, i) => i * 50)
  .duration(500)
  .attr("cy", d => yScale(d.value));
```

## Scales Reference

| Scale Type | Use Case |
|------------|----------|
| `scaleLinear` | 연속 수치 |
| `scaleLog` | 지수 데이터 |
| `scaleTime` | 시간/날짜 |
| `scaleBand` | Bar chart 카테고리 |
| `scaleOrdinal` | 색상 매핑 |
| `scaleSequential` | 연속 색상 |

## Color Schemes

```javascript
// Categorical
d3.schemeCategory10  // 10 colors
d3.schemeTableau10   // Tableau 10

// Sequential
d3.interpolateBlues
d3.interpolateYlOrRd

// Diverging
d3.interpolateRdBu
```

## Best Practices

1. **Data Validation**: null/NaN 체크
2. **Responsive**: ResizeObserver 사용
3. **Performance**: 1000+ 요소 시 Canvas 고려
4. **Accessibility**: ARIA labels 추가
5. **Clean Up**: 이전 렌더링 제거


---
Source attribution: chrisvoncsefalvay
Original project: https://github.com/aiskillstore/marketplace/blob/afd6c349bf0bfcbc38e5512b03314281ea117d42/skills/doyajin174/d3-viz/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: chrisvoncsefalvay
Original project: https://github.com/aiskillstore/marketplace/blob/afd6c349bf0bfcbc38e5512b03314281ea117d42/skills/doyajin174/d3-viz/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering, Design, Product Management
Roles: Data Analyst, Data Scientist, Frontend Developer, UX Designer, Product Manager
Specialties: Frontend, API, Cross Platform
Tools: D3.Js
Country applicability: Country not specified
Classification basis: Source category, role and specialization labels
Instruction SHA-256: 521fd174cffa2dac83a60b406903bf197916486b3abf216280cf60918c44651e