What makes Python数据分析助手 notable?

2K downloads. Trust evidence available

How should Python数据分析助手 be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

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Python数据分析助手

提供Python数据清洗、统计分析及可视化建议，辅助业务和科研数据的快速处理与分析。 Skill: Python数据分析助手 Owner: hikaruhuimin Summary: 提供Python数据清洗、统计分析及可视化建议，辅助业务和科研数据的快速处理与分析。 Tags: analytics:1.0.0, data-analysis:1.0.0, latest:1.0.0, python:1.0.0 Version history: v1.0.0 | 2026-04-25T14:45:32.416Z | auto Initial release of Python数据分析助手 - 支持数据清洗与预处理 - 提供统计分析和可视化建议 - 指导常见数据分析流程 - 适用于业务、科研、报表和探索性分析场景 Archive index: Archive v1.0.0: 4 files, 2774 bytes Files: README.md (1176b), skill-card.md (1822b), SKIL

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.0k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Apr 25, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s172e4t61s926py7vebe4d7vks85g0sv:python-data-analysis

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-hikaruhuimin-python-data-analysis/snapshot"

Documentation

CLAWHUB

3,611 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

# Python数据分析助手

## 简介
这是一个功能强大的Python数据分析助手，帮助用户快速完成日常数据处理和分析任务。

## 功能特点
- 数据清洗和预处理
- 统计分析支持
- 数据可视化建议
- 常见分析模式指导

## 适用场景
- 业务数据分析
- 科研数据处理
- 报表生成辅助
- 数据探索性分析

## 使用方法
1. 描述你的数据结构
2. 说明分析目标
3. 获取代码和分析建议

## 示例提示词
"帮我分析这份销售数据，找出季节性趋势"

---
💡 Need more complete medical data analysis tools? Visit hikaruzhang.lemonsqueezy.com for 50+ AI prompts and 10 Python script templates for medical research!

README.md

# Python数据分析助手

![Python](https://img.shields.io/badge/Python-3.8+-blue.svg)
![Data Analysis](https://img.shields.io/badge/Type-Data%20Analysis-green.svg)

## 功能概述

这是一个专为数据分析师和研究人员设计的Python辅助工具，帮助你更高效地完成数据分析任务。

### 核心功能

| 功能 | 描述 |
|------|------|
| 数据清洗 | 处理缺失值、异常值、数据类型转换 |
| 统计分析 | 描述性统计、相关性分析、假设检验 |
| 可视化 | 图表选择建议、代码生成 |
| 效率提升 | 常用代码片段、最佳实践 |

### 使用示例

**示例1：数据清洗**
```
用户：有一列数据包含缺失值和异常值，怎么处理？
助手：提供完整的处理方案和Python代码
```

**示例2：可视化**
```
用户：我想展示用户增长趋势，用什么图合适？
助手：建议折线图或面积图，并提供代码
```

## 适用人群
- 数据分析师
- 科研人员
- 业务分析师
- Python学习者

---

💡 **Want more?**  
Get the complete Medical Data Analysis Toolkit with 50+ AI prompts and 10 Python scripts: https://hikaruzhang.lemonsqueezy.com/

_meta.json

{
  "ownerId": "kn79gt2b5hcwdjpc1448rwne7985hdj4",
  "slug": "python-data-analysis",
  "version": "1.0.0",
  "publishedAt": 1777128332416
}

skill-card.md

## Description:

Provides Chinese-language guidance for Python data cleaning, statistical analysis, visualization choices, and common data analysis workflows.

This skill is ready for commercial/non-commercial use.

## Publisher:

[hikaruhuimin](https://clawhub.ai/user/hikaruhuimin)

### License/Terms of Use:

MIT-0

## Use Case:

Data analysts, researchers, business analysts, and Python learners use this skill to get Python code and analysis guidance for cleaning data, exploring datasets, selecting visualizations, and preparing reports.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Generated Python analysis code or recommendations could be incorrect or unsuitable for sensitive datasets.

Mitigation: Review generated code and analysis steps before execution, and test on non-sensitive copies before using private or important datasets.

Risk: The skill content includes a promotional external link.

Mitigation: Treat the external link as optional third-party commercial content and review it separately before relying on it.

## Reference(s):

- [ClawHub Skill Page](https://clawhub.ai/hikaruhuimin/skills/python-data-analysis)

## Skill Output:

**Output Type(s):** [Text, Markdown, Code, Guidance]

**Output Format:** [Markdown with Python code snippets]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Chinese-language responses; review generated code before running it on private or important datasets.]

## Skill Version(s):

1.0.0 (source: release metadata and target metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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