# Polars

> Fast in-memory DataFrame library for datasets that fit in RAM.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

- Page: https://ss33.ai/skills/oimiragieo/polars-33734971596
- Publisher: oimiragieo
- Category: [Data & Analytics](https://ss33.ai/skills/category/data-and-analytics-m1r3i9) › [Analysis & BI](https://ss33.ai/skills/category/data-and-analytics-m1r3i9/analysis-and-bi-b2nit8)
- Source: https://github.com/oimiragieo/agent-studio/blob/64b580eab27ba37673f042ecc12ac53413cd9dd5/.claude/skills/scientific-skills/skills/polars/SKILL.md

## Skill

This skill's licence does not allow redistribution, so the store does not serve its text. Get it from the author: https://github.com/oimiragieo/agent-studio/blob/64b580eab27ba37673f042ecc12ac53413cd9dd5/.claude/skills/scientific-skills/skills/polars/SKILL.md