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GitHub Skill

polars-expertise

This skill should be used when the user asks about Polars DataFrame library (Apache Arrow) for Python or Rust. Triggers: "polars expressions", "lazy vs eager", "scan_parquet streaming", "convert pandas to polars", "pyspark to polars", "kdb to polars", "group_by_dynamic", "rolling_mean", "polars window functions", "asof join", "polars GPU", "polars parquet", "LazyFrame". Time series: OHLCV resampling, rolling windows, financial data patterns. Performance: native expressions over map_elements, early projection, categorical types, streaming.

DeevsDeevs☆ 20 仓库 Stars5 仓库 Forks

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

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技能说明

功能与用途

This skill should be used when the user asks about Polars DataFrame library (Apache Arrow) for Python or Rust. Triggers: "polars expressions", "lazy vs eager", "scan_parquet streaming", "convert pandas to polars", "pyspark to polars", "kdb to polars", "group_by_dynamic", "rolling_mean", "polars window functions", "asof join", "polars GPU", "polars parquet", "LazyFrame". Time series: OHLCV resampling, rolling windows, financial data patterns. Performance: native expressions over map_elements, early projection, categorical types, streaming.

快速开始

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

使用指南 ↗

使用示例

查看来源仓库中的使用示例与配置说明。

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来源历史

收录时间
2026-01-20
索引更新时间
2026-02-13
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

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