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所在平台: Udemy |
课程主页: https://www.udemy.com/course/analyzing-data-with-polars-in-python/
课程评论：没有评论
**Coursera 课程总结：使用 Python Polars 进行数据分析** 本课程是一门关于如何利用 Polars——一个快速发展的开源 DataFrame 库——来加速数据分析的综合性课程。Polars 因其高效的性能，正成为 Python 数据科学领域越来越受欢迎的选择。 **课程内容概览：** * **入门与环境设置：** 欢迎学习者，指导如何安装 Polars 和必要的库，并解释 Polars 成为数据科学家首选的原因。 * **核心概念：** 深入理解 DataFrame 和 Series 等核心概念，掌握 Polars 如何简化数据分析和操作。 * **数据转换：** 学习如何高效地过滤行和列、更新数据以及添加新的行和列。 * **数据类型与缺失值：** 掌握处理数据类型（包括字符串和分类类型）、精度以及缺失值的方法，并学习处理嵌套数据结构。 * **文本转换：** 学习使用 Polars 进行格式化、替换、切片、过滤和拆分文本等操作。 * **统计与聚合：** 学习执行统计分析和聚合，包括计数、分组和计算分位数，以获得更深入的洞察。 * **合并 DataFrame：** 学习如何高效地连接 DataFrame，并执行左连接和内连接。 * **时间序列（日期和时间）：** 深入研究时间序列数据，包括时区、解析日期时间字符串、提取日期时间组件以及对时间序列数据进行分组操作。 * **输入与输出：** 掌握使用 Polars 读取各种来源的数据、选择和命名列以及将数据写入磁盘。 **目标学员：** * 希望摆脱传统电子表格限制，拥抱更敏捷高效的数据分析工具的数据分析师。 * Polars新手，希望快速上手这个强大 DataFrame 库的数据科学家。 * Pandas 或其他 DataFrame 库用户，想要探索更快速、更高效的数据分析工具。 **教学特色：** 本课程以 Jupyter Notebook 为载体，强调动手实践，对每个主题都进行了深入讲解。所有视频中展示的代码都作为 Jupyter Notebook 提供。学完本课程后，您将能够优化数据加载、处理和分析，成为一名熟练的 Polars 数据分析师，能够应对真实的 डेटा 挑战。
Speed up your data analysis with Polars, the rapidly growing open-source dataframe library that's gaining popularity among Python data scientists. This comprehensive course is your gateway to harnessing the power of Polars.What You Will Learn:- Introduction: Get started with a warm welcome and learn how to set up your environment by installing Polars and essential libraries. Discover why Polars is becoming the preferred choice for data scientists.- Core Concepts: Gain a solid foundation by exploring key concepts, including Series and DataFrames. Understand how Polars simplifies data analysis and manipulation.- Data Transformation: Dive into practical data manipulation. Learn how to filter rows and columns, update data, and add new columns and rows efficiently.- Data Types and Missing Values: Master the art of handling data types, precision, and missing values. Discover how Polars supports various data types, including string and categorical, and tackle nested data structures.- Text Transformation: Unlock the secrets of text manipulation using Polars. Format, replace, slice, filter, and split text with ease.- Statistics and Aggregations: Learn how to perform statistical analysis and aggregations. Count values, group data, and calculate quantiles to gain deeper insights.- Combining Dataframes: Explore the world of data integration by concatenating DataFrames and executing left and inner joins efficiently.- Timeseries (Dates and Time): Delve into timeseries data with Polars. Understand time zones, parse datetime strings, and extract datetime components. Perform operations on timeseries data and group it effectively.- Input and Output: Master data import and export with Polars. Read data from various sources, select and name columns, and write data to disk.Who This Course Is For:- Data analysts seeking to break free from the constraints of traditional spreadsheets and eager to embrace a more agile and efficient data analysis tool.- Data scientists new to Polars who want to quickly get up and running with this powerful dataframe library.- Users of Pandas or other dataframe libraries who want to explore a faster and more efficient data analysis tool.This course prioritizes hands-on learning through Jupyter notebooks, providing in-depth coverage of each topic. All code shown in the video is included as Jupyter notebooks. By the end of this course, you'll be equipped to optimize data loading, manipulation, and analysis, making you a proficient Polars data analyst ready to tackle real-world data challenges.
