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所在平台: Udemy |
课程主页: https://www.udemy.com/course/10-key-functions-to-analyze-data-in-python-for-beginners/
课程评论：没有评论
**课程名称：** Python数据分析入门：10个关键函数 **课程概述：** 本课程专为所有渴望用Python进行数据分析的学员设计，无论您是否有编程经验。您无需任何基础，只需准备一台电脑、网络连接和学习的意愿。 **课程需求：** 您需要设置Python环境，课程将指导您使用Anaconda（包含Jupyter Notebook）或Visual Studio Code等免费工具。 **课程内容：** 本课程将重点介绍10个Python中强大且实用的数据分析函数。每节课都将深入讲解一个函数的功能，并通过真实数据集演示其用法。您将学到： * 使用 `read_csv()` 和 `head()` 加载和查看数据 * 使用 `info()` 和 `describe()` 总结数据 * 使用 `dropna()` 和 `fillna()` 清理和处理缺失数据 * 使用 `groupby()` 和 `sort_values()` 对数据进行分组和排序 * 使用 `query()` 过滤数据 * 使用 `merge()` 合并数据集 **学习成果：** 课程结束后，您将不仅理解所学的函数，还能独立运用这10个函数对自己的数据集进行分析，并掌握基本的数据分析技能。
Welcome to "10 Awesome Functions in Python to Analyze Data"!Who this Course is forThis course is tailored for anyone eager to step into the world of data analysis using Python, whether you have coding experience or not. There's no need for prior knowledge-just a computer, an internet connection, and a willingness to learn.What You NeedTo start analyzing data with Python, you will need to set up a Python environment on your computer. But don't worry - I'm here to help every step of the way. We'll be using tools like Anaconda (which includes Jupyter Notebooks) or Visual Studio Code, both of which are free and widely used for data analysis. What You'll LearnIn this class, you'll dive into 10 of the most powerful and practical functions in Python that are essential for data analysis. Each lesson focuses on a specific function, explaining its purpose and demonstrating how to use it with real-world datasets. By the end of the course, you'll have a solid toolkit of Python skills that you can apply directly to your own data projects. Here's what you'll cover:How to load and view data with read_csv() and head()Summarizing your data with info() and describe()Cleaning and handling missing data using dropna() and fillna()Grouping and sorting data with groupby() and sort_values()Filtering data with query()Combining datasets using merge()By the end of this class you will not only understand the methods presented but also be able to apply the 10 functions on your own datasets and have gained great skills regarding data analysis.
