csv-analyzer

SKILL.md

CSV Analyzer

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

Usage

Quick stats

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

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

Top/Bottom N

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 2ฯƒ)

python3 {baseDir}/scripts/csv_analyze.py anomalies data.csv --column price

Group and aggregate

python3 {baseDir}/scripts/csv_analyze.py group data.csv --by category --agg "sum:amount" "count:id"

Features

  • ๐Ÿ“Š Automatic column type detection (numeric, date, text)
  • ๐Ÿ” Flexible filtering with comparison operators
  • ๐Ÿ“ˆ Statistical summary (mean, median, std, min, max, percentiles)
  • ๐Ÿšจ Anomaly detection (z-score based)
  • ๐Ÿ“‹ Grouping and aggregation
  • ๐Ÿ’พ Export filtered/processed results
  • ๐Ÿชถ Zero external dependencies โ€” 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)
Weekly Installs
3
First Seen
1 day ago
Installed on
openclaw3