polars
polars is an Exploratory analysis & notebooks skill for AI agents, published by DAAF-Contribution-Community in the daaf repository on GitHub. Skillspace rates polars D (66/100) and it passed the safety scan; the rating is based on static analysis only.
High-performance data manipulation with lazy/eager execution, expressions, I/O (CSV, Parquet, JSON), aggregations, joins, string/datetime ops, and pandas interop. Covers performance optimization patterns and common anti-patterns. DAAF's default DataFrame library — all pipeline code uses Polars, not pandas. Use for any DataFrame operation, reading/writing Parquet files, or migrating existing pandas code to Polars. R equivalent: tidyverse (use when execution language is R).
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 220
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- LGPL-3.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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