# Polars

> High-performance DataFrame library usage. Covers Lazy API, Wrangling, Aggregation.

- Skill: `yonesuke/polars` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add yonesuke/polars`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yonesuke/polars/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: yonesuke (https://skillmd.com/u/yonesuke)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/yonesuke/polars

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# Polars Skill

Fast data manipulation in Python.

## Contents

- [Examples](examples.md)
    - Lazy API, GroupBy, Window Functions.

## Core Concepts

- **Lazy API**: `df.lazy()...collect()`. Preferred for performance (Query Optimization).
- **Expressions**: `pl.col("a") * 2`. Parallelizable logic.
- **Eager API**: `df.filter(...)`. Good for debugging.

## Usage

Use for all tabular data tasks unless `pandas` is strictly required by legacy dependencies.