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.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill polarsnpx skills add K-Dense-AI/scientific-agent-skills --skill polars -a claude-code -gnpx skills add K-Dense-AI/scientific-agent-skills --skill polars -a codex -ggemini skills install https://github.com/K-Dense-AI/scientific-agent-skills.git --path scientific-skills/polarsgh skill install K-Dense-AI/scientific-agent-skills polarsgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills /tmp/K-Dense-AI__scientific-agent-skills
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/K-Dense-AI__scientific-agent-skills/scientific-skills/polars ~/.claude/skills/polars # Claude Code
cp -R /tmp/K-Dense-AI__scientific-agent-skills/scientific-skills/polars ~/.agents/skills/polars # Codex, Cursor, Gemini CLI, Copilot, OpenCode