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utopiabenben

Data Chart Tool

by utopiabenben · GitHub ↗ · v1.1.0-premium · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install data-chart-tool
Description
数据可视化工具,将 CSV/JSON 数据生成美观图表(柱状图、折线图、饼图等),配合 tushare-finance、财务分析、数据报告使用!
README (SKILL.md)

💎 付费功能(一次性购买,永久使用)

免费版功能

  • ✅ 柱状图(bar)、折线图(line)、饼图(pie)、面积图(area)
  • ✅ 基础自定义(标题、标签、颜色)
  • ✅ 批量处理
  • ✅ PNG/JPEG/PDF/SVG 输出
  • ✅ 预设样式(seaborn、ggplot 等)

专业版功能(¥99 一次性付费)

  • 散点图(scatter)—— 唯一付费图表类型
  • ✅ 无限制批量导出(无文件数量限制)
  • ✅ 优先技术支持
  • ✅ 未来所有新图表类型免费解锁

购买流程

  1. 扫码支付(微信/支付宝): ![收款码预留位置]
  2. 发送付款凭证:通过 OpenClaw 或 GitHub 联系我
  3. 接收许可证:我会发送 license.json 文件
  4. 安装许可证
    # 复制到本地
    cp license.json ~/.data-chart-tool/license.json
    # 设置环境变量(密钥会随许可证发送)
    export SKILL_LICENSE_SECRET="your-secret-key"
    
  5. 使用付费功能
    # 散点图(付费功能)
    python source/data_visualizer.py -i data.csv -t scatter --x-col x --y-col y --license ~/.data-chart-tool/license.json
    

注意

  • 许可证有效期:永久(一次性购买)
  • 支持多设备:同一许可证可在个人多台机器上使用
  • 不包含:企业批量授权(需要另外洽谈)

🎯 为什么选择付费版?

散点图是数据分析中最常用的高级图表之一,用于:

  • 相关性分析(两个变量的关系)
  • 聚类观察
  • 异常值检测

免费版已满足 80% 日常需求,付费版解锁专业分析能力。


📦 版本历史

  • v1.1.0-premium(2026-03-22):新增付费模式和散点图功能,许可证系统
  • v1.0.1(2026-03-20):营销优化版
  • v1.0.0(2026-03-15):初始版本

data-chart-tool - 数据可视化工具

数据可视化工具,将 CSV/JSON 数据生成美观图表,支持多种图表类型和输出格式!

功能特性

  • 读取多种数据格式:CSV、JSON、Excel
  • 多种图表类型:柱状图、折线图、饼图、散点图、面积图
  • 自定义样式:标题、标签、颜色、字体、图例
  • 多种输出格式:PNG、JPEG、PDF、SVG
  • 预览模式:显示图表而不保存文件
  • 批量处理:支持处理多个数据文件
  • 配合 tushare-finance:直接可视化股票数据

安装

# 安装依赖
pip install matplotlib pandas openpyxl

使用方法

基本用法

# 从 CSV 文件生成折线图
python source/data_visualizer.py --input data.csv --type line

# 从 JSON 文件生成柱状图
python source/data_visualizer.py --input data.json --type bar

# 生成饼图
python source/data_visualizer.py --input data.csv --type pie

# 预览模式(显示图表)
python source/data_visualizer.py --input data.csv --type line --preview

# 保存为 PDF
python source/data_visualizer.py --input data.csv --type line --output chart.pdf

详细参数

--input INPUT, -i INPUT     输入数据文件(CSV/JSON/Excel)
--type TYPE, -t TYPE        图表类型:bar(柱状图)、line(折线图)、pie(饼图)、scatter(散点图)、area(面积图)
--output OUTPUT, -o OUTPUT  输出文件路径(默认:chart.png)
--title TITLE                图表标题
--x-label X_LABEL            X 轴标签
--y-label Y_LABEL            Y 轴标签
--x-col X_COL                X 轴数据列名
--y-col Y_COL                Y 轴数据列名(逗号分隔多列)
--color COLOR                颜色(十六进制或颜色名)
--figsize FIGSIZE            图表大小,格式:宽,高(默认:10,6)
--dpi DPI                    输出 DPI(默认:100)
--grid, -g                   显示网格线
--legend, -l                 显示图例
--preview, -p                预览模式,显示图表不保存
--style STYLE                图表样式:default、seaborn、ggplot、fivethirtyeight

示例

# 股票数据可视化(配合 tushare-finance)
python source/data_visualizer.py -i stock_data.csv -t line --title "股票走势" --x-col "date" --y-col "close"

# 多列数据对比
python source/data_visualizer.py -i sales.csv -t bar --title "月度销售额" --x-col "month" --y-col "sales,profit" --legend

# 饼图展示占比
python source/data_visualizer.py -i category.csv -t pie --title "分类占比" --x-col "category" --y-col "value"

# 使用 seaborn 样式
python source/data_visualizer.py -i data.csv -t line --style seaborn --grid

# 保存为高分辨率 PDF
python source/data_visualizer.py -i data.csv -t bar --output report.pdf --dpi 300

支持的数据格式

  • CSV:逗号分隔值文件
  • JSON:JSON 格式数据(数组或对象)
  • Excel:.xlsx 和 .xls 格式

图表样式

  • default:默认样式
  • seaborn:Seaborn 风格
  • ggplot:ggplot 风格
  • fivethirtyeight:FiveThirtyEight 风格

配合 tushare-finance 使用

# 1. 先用 tushare-finance 获取数据
tushare stock_daily --ts_code 000001.SZ --start_date 20240101 --end_date 20241231 -o stock_data.csv

# 2. 再用 data-visualizer 可视化
python source/data_visualizer.py -i stock_data.csv -t line --title "平安银行股价走势" --x-col "trade_date" --y-col "close" --grid
Usage Guidance
This skill mostly does what it says (generating charts) and installs only common Python packages, but there are a few things to check before installing or paying: - Clarify the license secret: skill.json references SKILL_LICENSE_SECRET, the docs tell you to set it, but registry metadata listed no required env vars. Ask the author why the registry metadata omits this and what the secret actually is. Do NOT set any sensitive credentials (cloud keys, passwords) as SKILL_LICENSE_SECRET. - Verify the license workflow and the seller: payment is handled outside the platform (scan & send proof). That is manual and can be abused; only pay a seller you trust. Ask for the license file sample and verify it locally before trusting it. - Inspect or request the 'skills.shared.license_manager' implementation before enabling paid features. The code appends a workspace path and imports a shared module for license checks—if that module is provided by the platform it may be fine, but if an attacker can control it, it could run arbitrary code during license validation. If possible run the tool in an isolated environment (VM/container) first. - If you want extra assurance, run a quick code review of source/data_visualizer.py and any license_manager code, or run the script against non-sensitive sample data. Avoid using production/private data until you confirm behavior. If you provide the skills.shared/ license_manager implementation (or confirm the platform supplies it), I can re-evaluate and raise or lower the risk rating.
Capability Analysis
Type: OpenClaw Skill Name: data-chart-tool Version: 1.1.0-premium The data-chart-tool is a legitimate utility for generating visualizations (bar, line, pie, etc.) from CSV, JSON, and Excel files using pandas and matplotlib. While it implements a 'premium' monetization model that requires a license key for scatter plots, the code logic in source/data_visualizer.py is transparent, lacks network communication, and does not perform any unauthorized data access or execution. The installation script (install.sh) only fetches standard Python dependencies, and the license verification process is handled locally via a shared module.
Capability Assessment
Purpose & Capability
The code and SKILL.md implement CSV/JSON/Excel → charts and require typical Python packages (matplotlib, pandas, openpyxl), which matches the description. However skill.json declares a license_secret_env (SKILL_LICENSE_SECRET) while the registry metadata listed 'required env vars: none' — a mismatch that should be clarified.
Instruction Scope
Runtime instructions and the CLI stay within data-visualization scope (read input files, draw and save/preview charts). The SKILL.md asks users to place a license.json under ~/.data-chart-tool and set SKILL_LICENSE_SECRET. The Python code modifies sys.path to import skills.shared.license_manager from a workspace 'shared' module if present; this is unusual (depends on platform-provided shared code) and grants the skill discretion to use external shared code for license validation.
Install Mechanism
No remote downloads or obscure installers: install.sh runs pip install for common packages (matplotlib, pandas, openpyxl). That is an expected, low-risk install mechanism.
Credentials
The only secret-like item is SKILL_LICENSE_SECRET used for offline license verification. Requesting an environment variable for license verification is plausible, but the registry header said no required env vars while skill.json includes license_secret_env—this inconsistency should be resolved. The license secret itself should not be a general-purpose credential; do not reuse sensitive secrets (AWS keys, passwords) here.
Persistence & Privilege
always is false and the skill does not request system-wide persistence. It asks users to store a license file under ~/.data-chart-tool (user-level) which is normal for a local license. The code's sys.path modification is not persistence itself but does allow importing workspace-level shared modules—this is notable but not necessarily privileged.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install data-chart-tool
  3. After installation, invoke the skill by name or use /data-chart-tool
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0-premium
商业化试点版本:新增付费模式,散点图付费解锁。免费版完整保留,付费版支持散点图和无限批量导出。引入许可证验证系统(offline HMAC-SHA256)。
v1.0.1
优化ClawHub描述:突出专业图表生成和tushare集成
v1.0.0
data-chart-tool 1.0.0 - 首次发布:数据可视化工具,支持将 CSV/JSON/Excel 数据生成多类型美观图表 - 支持柱状图、折线图、饼图、散点图、面积图等类型 - 图表样式、标签、颜色、图例等多项自定义选项 - 多种输出格式支持:PNG、JPEG、PDF、SVG - 兼容 tushare-finance,方便财务与股票数据可视化 - 支持批量处理与预览模式
Metadata
Slug data-chart-tool
Version 1.1.0-premium
License MIT-0
All-time Installs 4
Active Installs 4
Total Versions 3
Frequently Asked Questions

What is Data Chart Tool?

数据可视化工具,将 CSV/JSON 数据生成美观图表(柱状图、折线图、饼图等),配合 tushare-finance、财务分析、数据报告使用!. It is an AI Agent Skill for Claude Code / OpenClaw, with 383 downloads so far.

How do I install Data Chart Tool?

Run "/install data-chart-tool" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Data Chart Tool free?

Yes, Data Chart Tool is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Data Chart Tool support?

Data Chart Tool is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Data Chart Tool?

It is built and maintained by utopiabenben (@utopiabenben); the current version is v1.1.0-premium.

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