{"slug":"sickn33-polars","source_name":"sickn33/polars","name":"Sickn33/Polars","description":"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.","version":1,"lift":{"pass_rate_delta_pts":9.09,"pass_rate_pct":100,"total_cases":22,"passed_cases":22,"tokens_delta_pct":202.3,"turns_delta_pct":0,"verdict":"pass","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-09T20:27:31.336000+00:00"},"skill_score":1,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":9.09,"with_pass_pct":100,"without_pass_pct":90.9,"tokens_delta_pct":202.3,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"pass","never_hurt":true,"completed_at":"2026-08-09T20:27:31.336000+00:00","run_id":"75402e3c-b080-4781-90c4-92b395213f2c","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"https://github.com/pola-rs/polars/blob/main/LICENSE","install_count":0,"manifest_hash":"decb15238caf477a71904ed1828e625b7e403c654cb487a69bd79b0408823381","raw_url":"https://app.decimal.ai/s/sickn33-polars/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/sickn33-polars"}