Polars 完全实战指南:下一代 Python DataFrame 库从入门到精通
全面掌握 Polars——用 Rust 打造的下一代 Python 数据处理库。从表达式系统、惰性求值到查询优化,大量实战代码手把手教学,并与 Pandas 进行真实性能对比,帮你找到最合适的数据工具。
Marcus is an analytics engineer with 9 years in the dbt and warehouse-modeling trenches. He spent three years at dbt Labs as a senior solutions architect helping enterprise customers (a large US bank, two telecom carriers) untangle 4000-model projects, and before that ran the analytics platform at HelloFresh's North America org where he rebuilt the supply-chain mart on Snowflake + dbt. His writing focuses on dbt project structure at scale, incremental model patterns that actually survive backfills, and the unglamorous work of column-level lineage and contract testing. He is a regular contributor to the dbt-utils package and co-maintains a small open-source linter for SQL style. Marcus lives in Berlin, holds a master's in statistics from UNC Chapel Hill, and roasts his own coffee badly.
全面掌握 Polars——用 Rust 打造的下一代 Python 数据处理库。从表达式系统、惰性求值到查询优化,大量实战代码手把手教学,并与 Pandas 进行真实性能对比,帮你找到最合适的数据工具。
实战拆解 scikit-learn 1.8 七大核心新特性:通过 Array API 实现 GPU 10倍加速、免GIL自由线程真正多核并行、温度缩放校准、Gap Safe Screening 高维加速、经典多维缩放等,附完整代码示例。