Token导航 LogoToken导航

Agent Skill · AI 工具

d3-visualization(d3 可视化)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

d3-visualization 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描有提醒项,按安装量在AI 工具类的 2,536 个 Skill 里排第 904。

总安装 1,681周安装 68GitHub Stars 85下载 528核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:d3-visualization(d3 可视化)
来源仓库:https://github.com/lyndonkl/claude
仓库路径:skills/d3-visualization
安装命令:
npx skills add https://github.com/lyndonkl/claude --skill d3-visualization
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/lyndonkl/claude --skill d3-visualization

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

d3-visualization 辅助数据整理、指标计算和图表准备工作。支持 CSV/Excel 清洗、异常检测和统计口径生成。适合将原始数据转化为可读性强的分析报告。使用时需明确数据来源和时间范围边界。敏感数据处理应提前确认脱敏策略。

d3-visualization 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/d3-visualization

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/lyndonkl/claude --skill d3-visualization;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

d3-visualization 怎么安装?

在终端执行 npx skills add https://github.com/lyndonkl/claude --skill d3-visualization。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

d3-visualization 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

d3-visualization 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

d3-visualization 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

d3-visualization 用的人多吗?

公开数据是累计安装 1,681 次,近一周安装 68 次,下载 528 次,GitHub 85 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

d3-visualization 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
d3-visualization

d3 可视化 · 本页

1,68185需要联网MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

D3.js Data Visualization

Table of Contents

- Create Basic Chart Workflow - Update Visualization with New Data - Create Advanced Layout Workflow


Overview

D3 provides low-level building blocks for data-driven DOM manipulation, visual encoding, layout algorithms, and interactions — enabling bespoke visualizations that chart libraries cannot provide.

Use D3 when: Chart libraries lack your specific design, you need full customization, you're building network graphs/hierarchies/maps, or animating data changes smoothly.

Prefer simpler tools when: Simple bar/line charts suffice (Chart.js, Highcharts), you need 3D (Three.js, WebGL), or datasets exceed 10K points without aggregation.

Core concepts: Data Joins (bind arrays to DOM elements), Scales (data values to visual values), Shapes (SVG path generation), Layouts (position calculation for networks/trees/maps), Transitions (animated state changes), Interactions (zoom/pan/drag/brush).

Skill Structure


Workflows

Choose a workflow based on your current task:

Create Basic Chart Workflow

Use when: Building bar, line, or scatter charts from scratch

Time: 1-2 hours

Copy this checklist and track your progress:

Basic Chart Progress:
- [ ] Step 1: Set up SVG container with margins
- [ ] Step 2: Load and parse data
- [ ] Step 3: Create scales (x, y)
- [ ] Step 4: Generate axes
- [ ] Step 5: Bind data and create visual elements
- [ ] Step 6: Style and add interactivity

Step 1: Set up SVG container with margins

Create SVG element with proper dimensions. Define margins for axes: {top: 20, right: 20, bottom: 30, left: 40}. Calculate inner width/height: width - margin.left - margin.right. See Getting Started.

Step 2: Load and parse data

Use d3.csv('data.csv') for external files or define data array directly. Parse dates with d3.timeParse('%Y-%m-%d') for time series. Convert strings to numbers for CSV data using conversion function. See Getting Started.

Step 3: Create scales

Choose scale types based on data: scaleBand (categorical), scaleTime (temporal), scaleLinear (quantitative). Set domains from data using d3.extent(), d3.max(), or manual ranges. Set ranges from SVG dimensions. See Scales & Axes.

Step 4: Generate axes

Create axis generators: d3.axisBottom(xScale), d3.axisLeft(yScale). Append g elements positioned with transforms. Call axis generators: .call(axis). Customize ticks with .ticks(), .tickFormat(). See Scales & Axes.

Step 5: Bind data and create visual elements

Use data join pattern: svg.selectAll(type).data(array).join(type). Set attributes using scales and accessor functions: .attr('x', d => xScale(d.category)). For line charts, use d3.line() generator. For scatter plots, create circles with cx, cy, r attributes. See Selections & Data Joins and Shapes & Layouts.

Step 6: Style and add interactivity

Apply colors: .attr('fill',...), .attr('stroke',...). Add hover effects: .on('mouseover',...) with tooltip. Add click handlers for drill-down. Apply transitions for initial animation (optional). See Transitions & Interactions and Common Patterns.


Update Visualization with New Data

Use when: Refreshing charts with new data (real-time, filters, user interactions)

Time: 30 minutes - 1 hour

Copy this checklist:

Update Progress:
- [ ] Step 1: Encapsulate visualization in update function
- [ ] Step 2: Update scale domains if needed
- [ ] Step 3: Re-bind data with key function
- [ ] Step 4: Add transitions to join
- [ ] Step 5: Update attributes with new values
- [ ] Step 6: Trigger update on data change

Step 1: Encapsulate visualization in update function

Wrap steps 3-5 from basic chart workflow in function update(newData) {...}. This makes visualization reusable for any dataset. See Workflows.

Step 2: Update scale domains

Recalculate domains when data range changes: yScale.domain([0, d3.max(newData, d => d.value)]). Update axes with transition: svg.select('.y-axis').transition().duration(500).call(yAxis). See Selections & Data Joins.

Step 3: Re-bind data with key function

Use key function for object constancy: .data(newData, d => d.id). Ensures elements track data items, not array positions. Critical for correct transitions. See Selections & Data Joins.

Step 4: Add transitions to join

Insert .transition().duration(500) before attribute updates. Specify easing with .ease(d3.easeCubicOut). For custom enter/exit effects, use enter/exit functions in .join(). See Transitions & Interactions.

Step 5: Update attributes with new values

Set positions/sizes using updated scales: .attr('y', d => yScale(d.value)), .attr('height', d => height - yScale(d.value)). Transitions animate from old to new values. See Common Patterns.

Step 6: Trigger update on data change

Call update(newData) when data changes: button clicks, timers (setInterval), WebSocket messages, API responses. For real-time, use sliding window to limit data points. See Workflows.


Create Advanced Layout Workflow

Use when: Building network graphs, hierarchies, or geographic maps

Time: 2-4 hours

Copy this checklist:

Advanced Layout Progress:
- [ ] Step 1: Choose appropriate layout type
- [ ] Step 2: Prepare and structure data
- [ ] Step 3: Create and configure layout
- [ ] Step 4: Apply layout to data
- [ ] Step 5: Bind computed properties to elements
- [ ] Step 6: Add interactions (drag, zoom)

Step 1: Choose appropriate layout type

Force Simulation: Network diagrams, organic clustering. Hierarchies: Tree, cluster (node-link), treemap, pack, partition (space-filling). Geographic: Maps with projections. Chord: Flow diagrams. See Advanced Layouts for decision guidance.

Step 2: Prepare and structure data

Force: nodes = [{id, group}], links = [{source, target}]. Hierarchy: Nested objects with children arrays, convert with d3.hierarchy(data). Geographic: GeoJSON features. See Advanced Layouts.

Step 3: Create and configure layout

Force: d3.forceSimulation(nodes).force('link', d3.forceLink(links)).force('charge', d3.forceManyBody()). Hierarchy: d3.treemap().size([width, height]). Geographic: d3.geoMercator().fitExtent([[0,0], [width,height]], geojson). See Advanced Layouts for each layout type.

Step 4: Apply layout to data

Force: Simulation runs automatically, updates node positions each tick. Hierarchy: Call layout on root: treemap(root). Geographic: No application needed, projection used in path generator. See Advanced Layouts.

Step 5: Bind computed properties to elements

Force: Update cx, cy in tick handler: node.attr('cx', d => d.x). Hierarchy: Use d.x0, d.x1, d.y0, d.y1 for rectangles. Geographic: Use path(feature) for d attribute. See Workflows for layout-specific examples.

Step 6: Add interactions

Drag for force networks: node.call(d3.drag().on('drag', dragHandler)). Zoom for maps/large networks: svg.call(d3.zoom().on('zoom', zoomHandler)). Click for hierarchy drill-down. See Transitions & Interactions.


Path Selection Menu

What would you like to do?

  1. I'm new to D3 - Setup environment, understand prerequisites, create first visualization
  2. Build a basic chart - Bar, line, or scatter plot step-by-step
  3. Transform data with scales - Map data values to visual properties (positions, colors, sizes)
  4. Bind data to elements - Connect arrays to DOM elements, handle dynamic updates
  5. Create network/hierarchy/map - Force-directed graphs, treemaps, geographic visualizations
  6. Add animations - Smooth transitions between chart states
  7. Add interactivity - Zoom, pan, drag, brush selection, tooltips
  8. Update chart with new data - Handle real-time data, filters, user interactions
  9. Get code templates - Copy-paste-modify templates for common patterns
  10. Understand D3 concepts - Deep dive into data joins, scales, generators, layouts

Quick Reference

Data Join Pattern (Core D3 Workflow)

// 1. Select container
const svg = d3.select('svg');

// 2. Bind data
svg.selectAll('circle')
  .data(dataArray)
  .join('circle')          // Create/update/remove elements automatically
    .attr('cx', d => d.x)  // Use accessor functions (d = datum, i = index)
    .attr('cy', d => d.y)
    .attr('r', 5);

Scale Creation (Data → Visual Transformation)

// For quantitative data
const xScale = d3.scaleLinear()
  .domain([0, 100])        // Data range
  .range([0, 500]);        // Pixel range

// For categorical data
const xScale = d3.scaleBand()
  .domain(['A', 'B', 'C'])
  .range([0, 500])
  .padding(0.1);

// For temporal data
const xScale = d3.scaleTime()
  .domain([new Date(2020, 0, 1), new Date(2020, 11, 31)])
  .range([0, 500]);

Shape Generators (SVG Path Creation)

// Line chart
const line = d3.line()
  .x(d => xScale(d.date))
  .y(d => yScale(d.value));

svg.append('path')
  .datum(data)           // Use .datum() for single data item
  .attr('d', line)       // Line generator creates path data
  .attr('fill', 'none')
  .attr('stroke', 'steelblue');

Transitions (Animation)

// Add transition before attribute updates
svg.selectAll('rect')
  .data(newData)
  .join('rect')
  .transition()          // Everything after this is animated
  .duration(500)         // Milliseconds
  .attr('height', d => yScale(d.value));

Common Scale Types

Data TypeTaskScale
Quantitative (linear)Position, sizescaleLinear()
Quantitative (exponential)Compress rangescaleLog(), scalePow()
Quantitative → Circle areaSize circlesscaleSqrt()
CategoricalBars, groupsscaleBand(), scalePoint()
Categorical → ColorsColor encodingscaleOrdinal()
TemporalTime seriesscaleTime()
Quantitative → ColorsHeatmapsscaleSequential()

D3 Module Imports (ES6)

// Specific functions
import { select, selectAll } from 'd3-selection';
import { scaleLinear, scaleBand } from 'd3-scale';
import { line, area } from 'd3-shape';

// Entire D3 namespace
import * as d3 from 'd3';

Key Resources by Task


Next Steps

  1. New to D3? Start with Getting Started
  2. Know basics? Jump to Workflows for specific chart types
  3. Need reference? Use Common Patterns for templates
  4. Build custom viz? Explore Advanced Layouts

平台分布

Claude Code

29.2%
按下载量换算154

Antigravity

24.14%
按下载量换算127

Gemini CLI

14.96%
按下载量换算79

windsurf

12.01%
按下载量换算63

OpenCode

8.22%
按下载量换算43

github-copilot

3.47%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

继续浏览同类 Skills