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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-a-data-analysis-library-from-scratch-in-python/
课程评论：没有评论
**课程名称：** 从零开始构建 Python 数据分析库 **课程概述：** 本课程专为希望深入学习 Python 高级概念并完成一个长而全面的项目的学习者设计。通过完成项目，你将构建一个功能齐全的 Python 库，能够执行许多常见的数据分析任务。该库将命名为“Pandas Cub”，并具有与流行的 Pandas 库相似的功能。 课程重点在于利用 Python 庞大的工具生态系统进行软件开发。课程包含 40 个详细步骤，每个步骤都要求你编写代码以增加库的功能。完成每个步骤的前提是通过预先编写好的单元测试。一旦所有单元测试通过，项目即告完成。近 100 个单元测试将为你提供关于代码是否正确完成各项任务的即时反馈。 **核心学习内容：** * **开发环境搭建：** 使用 Conda 创建开发环境。 * **测试驱动开发 (TDD)：** 运用 TDD 确保代码质量。 * **Python 数据模型：** 学习如何让自定义对象无缝兼容 Python 内建函数和运算符。 * **DataFrame 类构建：** 实现以下功能： * 使用方括号运算符选择数据子集。 * 聚合方法：sum, min, max, mean, median 等。 * 非聚合方法：isna, unique, rename, drop 等。 * 按一列或两列进行分组，创建数据透视表。 * 处理字符串列的特有方法。 * 从 CSV 文件读取数据。 * 在 notebook 中提供格式良好的 DataFrame 显示。 **课程目标：** 很多学习者可能只掌握了 Python 的基础操作，但缺乏完成大型项目或构建整个库的技能。本课程旨在为那些寻求一个具有挑战性、激动人心且需要付出大量努力和时间的项目的学生提供支持。 **讲师：** Ted Petrou，Pandas Cookbook、Master Data Analysis with Python 和 Master the Fundamentals of Python 的作者。
Build a Data a Data Analysis Library from Scratch in Python targets those that have a desire to immerse themselves in a single, long, and comprehensive project that covers several advanced Python concepts. By the end of the project you will have built a fully-functioning Python library that is able to complete many common data analysis tasks. The library will be titled Pandas Cub and have similar functionality to the popular pandas library.This course focuses on developing software within the massive ecosystem of tools available in Python. There are 40 detailed steps that you must complete in order to finish the project. During each step, you will be tasked with writing some code that adds functionality to the library. In order to complete each step, you must pass the unit-tests that have already been written. Once you pass all the unit tests, the project is complete. The nearly 100 unit tests give you immediate feedback on whether or not your code completes the steps correctly.There are many important concepts that you will learn while building Pandas Cub.Creating a development environment with condaUsing test-driven development to ensure code qualityUsing the Python data model to allow your objects to work seamlessly with builtin Python functions and operatorsBuild a DataFrame class with the following functionality:Select subsets of data with the brackets operatorAggregation methods - sum, min, max, mean, median, etc...Non-aggregation methods such as isna, unique, rename, dropGroup by one or two columns to create pivot tablesSpecific methods for handling string columnsRead in data from a comma-separated value fileA nicely formatted display of the DataFrame in the notebookIt is my experience that many people will learn just enough of a programming language like Python to complete basic tasks, but will not possess the skills to complete larger projects or build entire libraries. This course intends to provide a means for students looking for a challenging and exciting project that will take serious effort and a long time to complete. This course is taught by expert instructor Ted Petrou, author of Pandas Cookbook, Master Data Analysis with Python, and Master the Fundamentals of Python.
