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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ploars-python/
课程评论：没有评论
课程名称：Polars for Data Engineering - 数据框架新纪元 概述：本课程介绍了基于Polars的数据处理框架，旨在提升数据工程的性能。Polars是从基础构建而来，专注于性能，其多线程查询引擎使用Rust语言编写，设计为有效的并行处理。向量化和列式处理使得缓存一致的算法得以实现，能够在现代处理器上提供高性能。如果你对数据整理比较熟悉，使用Polars将让你感到得心应手。该框架的表达式直观，能够帮助你编写既可读又高效的代码。Polars是开源的，拥有活跃的开发者社区，鼓励用户添加新功能和贡献代码，基于MIT许可证免费使用。 课程重点是使用Python中的Polars进行ETL（提取、转换、加载）操作，涵盖Polars的基本知识，包括数据结构如Series和DataFrame，表达式，如选择功能、运算符、重命名列/字段及处理空值。还涉及各种转换操作，包括过滤、排序、连接、透视、拼接、熔化和窗口函数。Polars支持读取和写入所有常见的数据格式，从而便于与现有数据堆栈集成。支持的数据格式包括文本格式（CSV和JSON）、二进制格式（Parquet、Delta Lake、AVRO和Excel）、IPC格式（Feather和Arrow）、数据库（MySQL、Postgres、SQL Server、SQLite、Redshift和Oracle）以及云存储（S3、Azure Blob和Azure File）。
DataFrames For The New EraPolars is written from the ground up with performance in mind. Its multi-threaded query engine is written in Rust and designed for effective parallelism. Its vectorized and columnar processing enables cache-coherent algorithms and high performance on modern processors.You will feel right at home with Polars if you are familiar with data wrangling. Its expressions are intuitive and empower you to write code which is readable and performant at the same time.Polars is and always will be open source. Driven by an active community of developers, everyone is encouraged to add new features and contribute. Polars is free to use under the MIT license.The course is about performing ETL (Extract, Transform, Load) using Polars in Python. The course convers the basics of Polars, Data Structures in Polars such as Series, DataFrames,.., Expressions such as Select Functionality, Operators , Renaming the Columns/ Fields and Handling Nulls. Working with the Transformations such as Filter, Sort, Join, Pivot, Concatenate, Melts and Windowing Functions. Polars supports reading and writing to all common data formats. This allows you to easily integrate Polars with your existing data stack.Text: CSV & JSONBinary: Parquet, Delta Lake, AVRO & ExcelIPC: Feather, ArrowDatabases: MySQL, Postgres, SQL Server, Sqlite, Redshift & OracleCloud storage: S3, Azure Blob & Azure File
