exploring-data
// 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.
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 usereda_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.