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.
npx skills add majiayu000/claude-skill-registry --skill exploring-data --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Exploring Data ## Workflow ### 1. Check if installed (instant) ```bash bash /mnt/skills/user/exploring-data/scripts/check_install.sh ``` Returns: `installed` or `not_installed` ### 2. Install if needed (one-time, ~19s) ```bash if [ "$(bash check_install.sh)" = "not_installed" ]; then bash /mnt/skills/user/exploring-data/scripts/install_ydata.sh fi ``` ### 3. Run analysis (always generates JSON + HTML by default) ```bash bash /mnt/skills/user/exploring-data/scripts/analyze.sh <filepath> [minimal|full] [html|json] ``` **Defaults:** minimal + html (also generates JSON) **Output:** - `eda_report.html` - Interactive report for user - `eda_report.json` - Machine-readable for Claude analysis ### 4. If Claude needs to analyze (user asks "what do you think?" etc.) ```bash python /mnt/skills/user/exploring-data/scripts/summarize_insights.py /mnt/user-data/outputs/eda_report.json ``` **Reads:** `eda_report.json` (comprehensive ydata output) **Writes:** `eda_insights_summary.md` (condensed for Claude) **Outputs to stdout:** Formatted markdown summary Claude should read the stdout markdown summary, NOT the full JSON report. ## Invocation Examples ```bash # Standard workflow (user views HTML)
- Workflow
- 1. Check if installed (instant)
- 2. Install if needed (one-time, ~19s)
- 3. Run analysis (always generates JSON + HTML by default)
- 4. If Claude needs to analyze (user asks "what do you think?" etc.)
- Invocation Examples
- Modes
- User Triggers for Full Mode
bash /mnt/skills/user/exploring-data/scripts/check_install.sh if [ "$(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] python /mnt/skills/user/exploring-data/scripts/summarize_insights.py /mnt/user-data/outputs/eda_report.json Standard workflow (user views HTML) bash analyze.sh /mnt/user-data/uploads/data.csv Link user to: computer:///mnt/user-data/outputs/eda_report.html User asks Claude to analyze
What does the exploring-data skill do?
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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill exploring-data --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.