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ClaudeWave
Skill125 estrellas del repoactualizado today

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.

Instalar en Claude Code
Copiar
git clone --depth 1 https://github.com/oaustegard/claude-skills /tmp/exploring-data && cp -r /tmp/exploring-data/exploring-data ~/.claude/skills/exploring-data
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# 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)
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.
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