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ruiyongwang

Data Analysis Report

by ruiyongwang · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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/install data-analysis-report
Description
自动分析多种格式数据,生成含图表、关键洞察和建议的中文完整报告,支持本地安全处理和批量文件分析。
README (SKILL.md)

Data Analysis Report Generator (智能数据分析报告生成器)\r

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概述\r

专业的数据分析和报告生成技能,支持CSV、Excel、JSON等多种数据格式,自动生成包含图表、洞察和可执行建议的完整分析报告。\r \r

核心能力\r

  1. 数据自动分析:自动识别数据类型、异常值、相关性\r
  2. 智能可视化:自动选择合适的图表类型(柱状图、折线图、散点图等)\r
  3. 中文优化:对中文数据自动适配,输出中文报告\r
  4. 安全隐私:数据本地处理,不上传到第三方服务\r
  5. 批量处理:支持大文件处理和自动采样\r \r

技术架构\r

核心依赖库:\r
- pandas (数据处理和分析)\r
- matplotlib (基础图表生成)\r
- seaborn (美观统计图表)\r
- plotly (交互式图表)\r
- jupyter (报告生成环境)\r
```\r
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## 支持的数据格式\r
- CSV (.csv)\r
- Excel (.xlsx, .xls)\r
- JSON (.json)\r
- TSV (.tsv)\r
- DataFrame对象\r
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## 安装要求\r
```bash\r
安装Python依赖(已自动处理):\r
pip install pandas matplotlib seaborn plotly jupyter openpyxl\r
```\r
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## 使用指令/触发词\r
- "分析这个数据"\r
- "生成数据报告"\r
- "找出关键洞察"\r
- "数据可视化分析"\r
- "automatically analyze this data"\r
- "generate data insights report"\r
\r
## 详细功能说明\r
\r
### 数据质量检测\r
- 缺失值统计和可视化\r
- 异常值检测和报告\r
- 数据类型分布分析\r
- 数据完整性评估\r
\r
### 统计分析功能\r
- 描述性统计(均值、中位数、标准差等)\r
- 相关性分析(热力图显示)\r
- 趋势分析(时间序列)\r
- 分布分析(直方图、箱线图)\r
\r
### 报告生成能力\r
- **数据概览报告**:整体数据情况和质量评估\r
- **关键洞察摘要**:3-5个最重要的发现\r
- **详细分析报告**:每个维度的深入分析\r
- **可执行建议**:基于分析结果的优化建议\r
\r
## 应用场景示例\r
\r
### 1. 销售数据分析\r
```\r
触发:"分析这份销售数据报表"\r
输出:\r
- 月度/季度/年度趋势分析\r
- 畅销产品Top 10\r
- 地域分布热力图\r
- 销售渠道效果对比\r
- 客户购买行为分析\r
```\r
\r
### 2. 工程质量数据分析\r
```\r
触发:"分析这个项目的质量检测记录"\r
输出:\r
- 合格率趋势分析\r
- 主要问题帕累托图\r
- 整改完成情况\r
- 风险评估矩阵\r
```\r
\r
### 3. 成本分析报告\r
```\r
触发:"分析这份工程造价数据"\r
输出:\r
- 成本构成饼图\r
- 材料价格趋势分析\r
- 单项成本对比\r
- 超预算预警分析\r
```\r
\r
## 输出格式选项\r
- **HTML报告**:交互式网页报告,包含所有图表\r
- **PDF报告**:便于打印和分发的版本\r
- **Markdown总结**:简洁的文字总结\r
- **图表集合**:独立的图表文件集合\r
\r
## 高级功能\r
\r
### 自定义模板\r
支持用户上传自定义报告模板,包括:\r
- 企业品牌LOGO和配色\r
- 标准化报告结构\r
- 特定KPI计算逻辑\r
\r
### 批量处理\r
- 自动处理多个文件\r
- 合并多个数据源\r
- 生成统一的综合报告\r
\r
### 自动化调度\r
- 定时执行分析任务\r
- 邮件自动发送报告\r
- 系统集成API\r
\r
## 安全性说明\r
1. **数据本地处理**:所有数据处理都在您的本地环境完成\r
2. **无网络传输**:无需上传数据到云端\r
3. **权限控制**:遵循本地文件系统权限\r
4. **数据清理**:分析完成后可自动清理临时文件\r
\r
## 性能优化\r
- 大文件自动分块处理\r
- 智能内存管理\r
- 多线程数据处理\r
- 缓存机制加速重复分析\r
\r
## 兼容性\r
- **Python版本**:3.8+\r
- **操作系统**:Windows、macOS、Linux\r
- **集成平台**:OpenClaw、Claude Desktop、WorkBuddy\r
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## 更新日志\r
- 2026-04-03:初始版本发布\r
- 支持12种图表类型\r
- 优化中文报告输出\r
- 增强数据安全保护\r
\r
## 技术支持\r
如有问题或需要定制功能,请联系项目维护团队或查看项目GitHub仓库。\r
\r
---\r
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**注意**:本技能为开源项目,欢迎贡献代码和提出建议!
Usage Guidance
This skill appears internally consistent and implements local data analysis. Before installing: (1) run it inside a virtualenv or isolated environment and review/approve the pip installs; (2) if you plan to enable advanced features like scheduled runs or email sending, expect to supply credentials (SMTP/API keys) and review any added code for network transmission; (3) test on non-sensitive sample data first to confirm no unexpected external calls; (4) if you require a stricter install mechanism, ask the publisher for a formal install spec or packaged release.
Capability Analysis
Type: OpenClaw Skill Name: data-analysis-report Version: 1.0.0 The skill bundle provides standard data analysis and report generation functionality using pandas and numpy. The code in processors/data_processor.py implements basic statistical analysis, correlation detection, and Markdown report generation without any evidence of data exfiltration, network communication, or unauthorized file access. While SKILL.md mentions advanced features like email scheduling and API integration, the provided implementation is restricted to local processing and lacks any malicious or suspicious logic.
Capability Assessment
Purpose & Capability
Name/description promise local data analysis and report generation in Chinese. The included processor (processors/data_processor.py) implements CSV/DataFrame analysis, correlation/outlier detection and Markdown report generation, which aligns with the stated purpose. The SKILL.md lists common Python data libraries (pandas/matplotlib/seaborn/plotly) that are reasonable for this functionality. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
SKILL.md focuses on local processing and gives triggers and usage guidance. It instructs installing Python dependencies (pip install ...) but provides no runtime steps that read unrelated system files or environment variables. A minor scope note: the doc mentions advanced features like "邮件自动发送报告" (automatic email sending) and "系统集成API" which would require network access and credentials if enabled — however, there are no implementation or credential requests for those features in the provided code.
Install Mechanism
This is an instruction-only skill with one included Python file; there is no formal install spec. SKILL.md recommends 'pip install pandas matplotlib seaborn plotly jupyter openpyxl' — installing packages from PyPI is normal but should be done in a controlled environment (virtualenv/container). No downloads from arbitrary URLs or extract steps were found.
Credentials
The skill requires no environment variables, credentials, or config paths. The code does not read env vars or access external services. The lack of requested secrets is proportionate to the described functionality.
Persistence & Privilege
Flags are default (always: false, user-invocable, model invocation allowed). The skill does not request permanent presence or modify other skills/configs. No privileged persistence behavior was observed.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install data-analysis-report
  3. After installation, invoke the skill by name or use /data-analysis-report
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Data Analysis Report Generator 1.0.0 - Initial release with automated data analysis and report generation. - Supports CSV, Excel, JSON, TSV, and DataFrame formats. - Automatically generates charts, key insights, and actionable recommendations. - Optimized for Chinese-language datasets and outputs. - Ensures local data processing for privacy and security. - Offers batch processing, report template customization, and multiple output formats (HTML, PDF, Markdown, chart files).
Metadata
Slug data-analysis-report
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Data Analysis Report?

自动分析多种格式数据,生成含图表、关键洞察和建议的中文完整报告,支持本地安全处理和批量文件分析。 It is an AI Agent Skill for Claude Code / OpenClaw, with 201 downloads so far.

How do I install Data Analysis Report?

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

Is Data Analysis Report free?

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

Which platforms does Data Analysis Report support?

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

Who created Data Analysis Report?

It is built and maintained by ruiyongwang (@ruiyongwang); the current version is v1.0.0.

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