This comprehensive course equips learners with the skills to create, customize, and evaluate high-quality visualizations using Python’s Matplotlib library. Beginning with foundational plotting concepts, learners will identify key Matplotlib components, construct simple and multi-axis plots, and apply labeling, scaling, and annotation techniques to effectively convey data insights.
Mastering Data Visualization with Matplotlib
您将学到什么
Construct simple and multi-axis plots with labels, scaling, and annotations.
Design specialized charts including polar plots, streamplots, and pie charts.
Customize styles, axes, and figures to produce publication-ready visuals.
您将获得的技能
要了解的详细信息
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最近已更新！
September 2025
作业
8 项作业
授课语言：英语（English）
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本课程是 Matplotlib: Python Data Visualization & Wrangling 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
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该课程共有2个模块
This module introduces learners to the essential concepts and workflows of creating visualizations using Matplotlib. It covers the installation and setup of Python and Matplotlib, fundamental plotting commands, customization of simple plots, and managing figures and axes. Learners will develop the foundational skills necessary to create, modify, and interpret basic line graphs, preparing them for more advanced data visualization techniques.
涵盖的内容
12个视频4个作业
This module builds on foundational Matplotlib skills by exploring advanced chart types, specialized visuals, and customization techniques. Learners will work with complex plot elements such as custom line patterns, pseudocolor meshes, streamplots, ellipses, polar charts, and pie charts. They will also apply advanced styling to images, plots, and figure outputs using Matplotlib’s customization tools and style sheets, enabling them to produce visually refined, publication-ready visualizations.
涵盖的内容
15个视频4个作业
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When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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