|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/500-exercises-to-master-python-pandas/
课程评论：没有评论
**课程名称：** 500道练习精通Python Pandas **课程概述：** 本课程专为计划进入数据科学领域的初学者和中级数据分析师、数据科学家及数据工程师设计。课程中的大部分练习基于作者作为数据科学家处理真实数据集的经验，即使您在工作中已经使用Pandas，也能从中受益。对于Pandas初学者，练习的设计也力求简单易懂，能学到很多知识。您只需具备基础的Python知识即可。 **课程所需：** 课程以Jupyter Notebook的形式进行讲解，您需要在每节课的描述中找到相应的Notebook下载。为保证练习的顺利进行，请同时下载课程仓库中data文件夹内的相关数据集。您需要安装Jupyter Notebook，或者使用Google Colab（免费在浏览器中运行Jupyter Notebook）。 **课程结构：** 课程共分为六个章节： 1. **绪论** 2. **数据探索与处理** 3. **数据筛选** 4. **合并DataFrame** 5. **数据分析与可视化** 6. **用例** 7. **更多学习** 每个章节包含多个讲座，每个讲座侧重于特定任务，例如如何筛选DataFrame、如何创建多步骤的管道（pipelines），以及如何使用Python字典增强Pandas函数的功能。 **课程目标：** 完成本课程后，您将完成至少500个练习，并能够解决与表格数据相关的绝大多数任务。
Who is this course for?This course is for those who plan to take a step into the field of data science and beginner to intermediate level data analyst, data scientist, and data engineers. Most of the exercises are based on my experience of working as a data scientist with real-life datasets so you can benefit from this course even if you are already using Pandas at your job. If you have never used Pandas before or have little experience, you can learn a lot because the exercises are created in a way that is simple and easy-to-understand. All you need is a basic level of Python knowledge.What is needed to take this course?Lectures are structured as me going over Jupyter notebooks explaining exercises. Notebooks can be found in the description of each lecture. If you want to download the notebooks and follow along, make sure you also download the relevant datasets available in the data folder in the course repository. You also need to have Jupyter notebook installed on your computer. You can also Google Colab, which allows for running Jupyter notebooks in your browser for free. Course structureThe course is divided into 6 chapters:IntroductionData exploration and manipulationData filteringCombining DataFramesData analysis and visualizationUse casesMore learningsEach chapter contains multiple lectures with each one focusing on a particular task such as how to filter a DataFrame, how to create pipelines with multiple steps, and how to use Python dictionaries to enhance the power of Pandas functions.By the time you finish this course, you'll have solved at least 500 exercises and you'll be able to solve most of the tasks related to tabular data.
