菜单
Exploratory data analysis using ydata-profiling. Use when users upload .csv/.xlsx/.json/.parquet files or request "explore data", "analyze dataset", "EDA", "profile data". Generates interactive HTML or JSON reports with statistics, visualizations, correlations, and quality alerts.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/majiayu000/claude-skill-registry --skill exploring-data命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | exploring-data |
| description | Exploratory data analysis using ydata-profiling. Use when users upload .csv/.xlsx/.json/.parquet files or request "explore data", "analyze dataset", "EDA", "profile data". Generates interactive HTML or JSON reports with statistics, visualizations, correlations, and quality alerts. |
| metadata | {"version":"0.0.3"} |
bash /mnt/skills/user/exploring-data/scripts/check_install.sh
Returns: installed or not_installed
if [ "$(bash check_install.sh)" = "not_installed" ]; then
bash /mnt/skills/user/exploring-data/scripts/install_ydata.sh
fi
bash /mnt/skills/user/exploring-data/scripts/analyze.sh <filepath> [minimal|full] [html|json]
Defaults: minimal + html (also generates JSON)
Output:
eda_report.html - Interactive report for usereda_report.json - Machine-readable for Claude analysispython /mnt/skills/user/exploring-data/scripts/summarize_insights.py /mnt/user-data/outputs/eda_report.json
Reads: eda_report.json (comprehensive ydata output)
Writes: eda_insights_summary.md (condensed for Claude)
Outputs to stdout: Formatted markdown summary
Claude should read the stdout markdown summary, NOT the full JSON report.
# Standard workflow (user views HTML)
bash analyze.sh /mnt/user-data/uploads/data.csv
# Produces: eda_report.html + eda_report.json
# Link user to: computer:///mnt/user-data/outputs/eda_report.html
# User asks Claude to analyze
bash analyze.sh /mnt/user-data/uploads/data.csv
python summarize_insights.py /mnt/user-data/outputs/eda_report.json
# Claude reads the stdout markdown summary
# Claude can then provide analysis based on patterns/insights
# Full mode for comprehensive analysis
bash analyze.sh /mnt/user-data/uploads/data.csv full
# JSON-only output (skip HTML generation)
bash analyze.sh /mnt/user-data/uploads/data.csv minimal json
Minimal (default, 5-10s): Dataset overview, variable analysis, correlations, missing values, alerts
Full (10-20s): Everything in minimal + scatter matrices, sample data, character analysis, more visualizations
"comprehensive analysis", "detailed EDA", "full profiling", "deep analysis"
Otherwise use minimal.