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所在平台: Udemy |
课程主页: https://www.udemy.com/course/making-graphs-in-python-using-matplotlib-for-beginners/
课程评论：没有评论
**课程名称：** Python 数据可视化入门 (Data Visualization with Python for Beginners) **课程概述：** 本课程面向希望学习如何使用 Python 进行数据可视化的初学者。在当今世界和现代商业环境中，数据和分析变得日益重要。数据分析常常需要创建图表，这有助于更好地理解数据并有效地传达分析结果。Python 是数据专业人士的首选语言，并且在 Python 中进行数据分析也越来越普遍。因此，能够直接在分析的同时创建自定义图表是一项宝贵的技能。 本课程将从基础的 Python 环境设置开始，然后深入探讨不同类型的图表及其自定义方法。我们将从基本的折线图和散点图入手，帮助您熟悉相关库（Matplotlib），然后逐步学习创建更多样化的图表。您将学习如何添加误差线、如何使用颜色表示强度、如何在图表中使用图像，以及如何创建三维图。 此外，课程还将专门讲解 Matplotlib 提供的各种自定义选项，以便您能够修改坐标轴、刻度线和标签的外观，学习如何添加注释和数学公式，或者如何隐藏图表的特定部分，从而创建更简洁、更清晰的图表。
Data and analytics are becoming increasingly important in our world and in modern day businesses. Usually data analytics at one point or another also means including or creating graphics. This can help you get a better sense of the data as well as help you better communicate your findings to others.Python is a favourite among data professionals, and performing analytics in Python is becoming increasingly more common. Therefore, it's great to be able to also directly create custom graphs alongside all the analytics.In this course we'll start with some basic setup, and then get into different types of plots that we can create as well as how we can customize them.We'll start off covering basic line and scatter plots, just to get a hang of the library, and then move further to create a larger variety of graphs. You'll learn how to add error bars, how to use and represent colours for intensities, how to use images in your plots, as well as how to create 3d plots.Additionally, we'll spend some time looking at the customization options that Matplotlib provides, so that we can change the way our axes and axis ticks and labels look, learn how to add annotations and math formulas, or also how to hide parts of a graph so that we have a reduced and cleaner version.
