# CSV Analyzer

> Analyze CSV/Excel files with natural language. Get statistics, filter rows, find anomalies, generate summaries, and export results. No pandas needed — uses Python stdlib for lightweight operation.

- Skill: `dvcrn/csv-analyzer-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add dvcrn/csv-analyzer-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/csv-analyzer-2/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/dvcrn/csv-analyzer-2

---


# CSV Analyzer

Analyze CSV files with simple commands. Get instant statistics, filter data, detect anomalies, and export results — all without pandas or heavy dependencies.

## Usage

### Quick stats
```bash
python3 {baseDir}/scripts/csv_analyze.py stats data.csv
```
Shows row count, column types, min/max/mean for numeric columns, unique counts for text columns.

### Filter rows
```bash
python3 {baseDir}/scripts/csv_analyze.py filter data.csv --where "amount>1000" --output big_orders.csv
```

### Top/Bottom N
```bash
python3 {baseDir}/scripts/csv_analyze.py top data.csv --column revenue --n 10
python3 {baseDir}/scripts/csv_analyze.py bottom data.csv --column revenue --n 5
```

### Detect anomalies (values outside 2σ)
```bash
python3 {baseDir}/scripts/csv_analyze.py anomalies data.csv --column price
```

### Group and aggregate
```bash
python3 {baseDir}/scripts/csv_analyze.py group data.csv --by category --agg "sum:amount" "count:id"
```

## Features

- 📊 Automatic column type detection (numeric, date, text)
- 🔍 Flexible filtering with comparison operators
- 📈 Statistical summary (mean, median, std, min, max, percentiles)
- 🚨 Anomaly detection (z-score based)
- 📋 Grouping and aggregation
- 💾 Export filtered/processed results
- 🪶 **Zero external dependencies** — Python stdlib only (csv module)

## Dependencies

None! Uses only Python standard library.

## Why Not Pandas?

Pandas is great but:
- Takes 100MB+ RAM just to import
- Overkill for quick analysis tasks
- This skill runs on 2GB RAM servers without issues
- For truly large datasets, the agent can recommend installing pandas

## Limitations

- Designed for files up to ~100MB (loads into memory)
- For larger files, use streaming mode or install pandas
- Date parsing is basic (ISO format preferred)