exploring-data（探索数据）

Exploring Data

Workflow

1. Check if installed (instant)

bash /mnt/skills/user/exploring-data/scripts/check_install.sh

Returns: installed or not_installed

2. Install if needed (one-time, ~19s)

if [ "$(bash check_install.sh)" = "not_installed" ]; then
    bash /mnt/skills/user/exploring-data/scripts/install_ydata.sh
fi

3. Run analysis (always generates JSON + HTML by default)

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 user
• eda_report.json - Machine-readable for Claude analysis

4. If Claude needs to analyze (user asks "what do you think?" etc.)

python /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.

Invocation Examples

# 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

Modes

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

User Triggers for Full Mode

"comprehensive analysis", "detailed EDA", "full profiling", "deep analysis"

Otherwise use minimal.