How long does it take to complete the course?

The course is approximately 9 hours in duration, making it a relatively short yet intensive course for learning data visualization techniques with Python. Depending on your pace and whether you engage with quizzes and projects, the course can be completed in a few days or over a week.

Can I preview a course before enrolling?

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

When will I have access to the lectures and assignments?

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

What will I get when I enroll?

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Data Visualization and Storytelling with Python

Data Visualization and Storytelling with Python

本课程是 Data Understanding and Data Visualization with Python 专项课程的一部分

位教师：Packt - Course Instructors

包含在中

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6个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

6个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master Python libraries like Matplotlib, Seaborn, and Plotly for data visualization.
Create interactive and 3D visualizations with Bokeh and Plotly, and geographic maps with Folium.
Apply data visualization techniques to real-world business, research, and data analysis scenarios.

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Data Understanding and Data Visualization with Python 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。

向行业专家学习新概念
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通过实践项目培养工作相关技能
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该课程共有6个模块

This course features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive into the world of data visualization and learn to effectively communicate data insights using popular Python libraries. You will explore a wide range of tools such as Matplotlib, Seaborn, Bokeh, Plotly, and Folium to craft stunning visualizations and interactive plots. This course will equip you with the skills needed to visualize data across different domains—from simple 2D plots to complex 3D and geographic visualizations. Throughout the course, you will start by learning the basics of Matplotlib, including customizing plots, adding markers, and managing axis limits. Then, you will move into advanced topics like creating subplots, contour plots, and even 3D plots. You will also explore Seaborn for high-level visualization, including relational and categorical plots, heatmaps, and more. As you advance, you'll interact with tools like Bokeh and Plotly to make your plots interactive, and finally, you’ll learn to create geographic maps with Folium to visualize real-world data such as COVID-19 statistics. This course offers an interactive journey where each concept builds upon the last. You'll apply what you learn in quizzes and real-world projects, allowing you to strengthen your skills progressively. You'll also benefit from hands-on projects, such as working with 3D surface plots and geographical data, which will allow you to test your skills and deepen your understanding. This course is designed for individuals who are looking to enhance their data visualization skills with Python. It is ideal for beginners to intermediate learners in data science, computer science, or anyone looking to better present and interpret data insights. Familiarity with Python programming basics is recommended but not required. By the end of the course, you will be able to create various types of visualizations—from simple line plots to complex interactive 3D scatter plots and geographical maps—and understand how to choose the right type of plot for your data and audience.

In this module, we will introduce you to the powerful Matplotlib library and its wide range of visualization capabilities. You will learn how to create multiple types of plots, customize them for better presentation, and add meaningful annotations. By the end of this section, you’ll be equipped to build and tailor plots that effectively communicate insights from your data.

涵盖的内容

28个视频2篇阅读材料1个作业

28个视频总计165分钟

Introduction to Matplotlib5分钟
Matplotlib Multiple Plots9分钟
Matplotlib Colors and Styles8分钟
Matplotlib Colors and Styles Quiz1分钟
Matplotlib Colors and Styles Solution4分钟
Matplotlib Colors and Styles Shortcuts8分钟
Matplotlib Axis Limits11分钟
Matplotlib Axis Limits Quiz1分钟
Matplotlib Axis Limits Solution2分钟
Matplotlib Legends Labels6分钟
Matplotlib Set Function5分钟
Matplotlib Set Function Quiz1分钟
Matplotlib Set Function Solution4分钟
Matplotlib Markers8分钟
Matplotlib Markers Random Plots6分钟
Matplotlib Scatter Plot12分钟
Matplotlib Contour Plot9分钟
Matplotlib Contour Plot Quiz1分钟
Matplotlib Contour Plot Solution4分钟
Matplotlib Histograms8分钟
Matplotlib Subplots10分钟
Matplotlib Subplots Quiz1分钟
Matplotlib Subplots Solution5分钟
Matplotlib 3D Introduction6分钟
Matplotlib 3D Scatter Plots5分钟
Matplotlib 3D Scatter Plot Quiz1分钟
Matplotlib 3D Scatter Plot Solution4分钟
Matplotlib 3D Surface Plots8分钟

2篇阅读材料总计20分钟

Introduction to the Course 'Data Visualization and Storytelling with Python'10分钟
Full Specialization Resources10分钟

1个作业总计15分钟

Matplotlib for Data Visualization - Assessment15分钟

In this module, we will explore Seaborn, a high-level visualization library that builds on Matplotlib’s functionality. You will discover how to make beautiful, informative plots with minimal code and learn techniques for visualizing both categorical and continuous data. By the end of this section, you’ll be proficient in using Seaborn to create aesthetically pleasing and insightful visualizations.

涵盖的内容

10个视频1个作业

10个视频总计49分钟

Introduction to Seaborn11分钟
Seaborn Relplot4分钟
Seaborn Relplot Quiz1分钟
Seaborn Relplot Solution4分钟
Seaborn Relplot Kind Line5分钟
Seaborn Relplot Facets9分钟
Seaborn Relplot Facets Quiz1分钟
Seaborn Relplot Facets Solution2分钟
Seaborn Catplot5分钟
Seaborn Heatmaps3分钟

1个作业总计15分钟

Seaborn for Data Visualization - Assessment15分钟

In this module, we will introduce you to Bokeh, a powerful library for creating interactive visualizations. You’ll learn how to design interactive plots that allow users to engage with the data in real time. Whether you’re building dashboards or exploring relationships, this module will empower you to create dynamic visualizations for your audience.

涵盖的内容

5个视频1个作业

In this module, we will dive into 3D interactive plotting using Plotly. You’ll learn how to create and manipulate 3D scatter plots and surface plots to better understand complex relationships within your data. By the end of this section, you’ll have the skills to develop interactive, 3D visualizations that bring your data to life.

涵盖的内容

6个视频1个作业

6个视频总计26分钟

Plotly 3D Interactive Scatter Plot7分钟
Plotly 3D Interactive Scatter Plot Quiz1分钟
Plotly 3D Interactive Scatter Plot Solution5分钟
Plotly 3D Interactive Surface Plot5分钟
Plotly 3D Interactive Surface Plot Quiz1分钟
Plotly 3D Interactive Surface Plot Solution5分钟

1个作业总计15分钟

Plotly for 3D Interactive Plotting - Assessment15分钟

In this module, we will explore how to use Folium for creating interactive geographic maps. You will learn how to integrate real-world data, such as COVID-19 statistics, into your maps and customize them for maximum clarity and engagement. This section will give you the tools to bring geographic data to life in an interactive way.

涵盖的内容

3个视频1个作业

In this module, we will show you how to use Pandas for quick and effective data visualization. You’ll learn to generate basic plots such as line and bar charts directly from your DataFrame, making it easier to analyze and interpret data without additional libraries. By the end of this section, you’ll be able to leverage Pandas for both analysis and visualization in one seamless workflow.

涵盖的内容

2个视频1篇阅读材料3个作业

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常见问题

Data Visualization and Storytelling with Python is a course that teaches you how to effectively communicate data insights through various visualization techniques using Python. By leveraging popular libraries like Matplotlib, Seaborn, Plotly, and others, you'll learn how to create interactive and engaging visuals. This is particularly relevant today, as data-driven decision-making has become crucial across industries. The ability to visualize data clearly allows for better understanding, exploration, and presentation of data, making it easier to identify trends and make informed decisions.

This course is part of the Data Visualization and Storytelling with Python specialization, which is designed to help you master the tools and techniques necessary for creating meaningful data visualizations. The course covers various libraries, including Matplotlib, Seaborn, Plotly, Bokeh, and Folium, and guides you through different types of plots, from simple bar charts to interactive 3D visualizations and geographic maps. You’ll also learn how to tell a compelling story with your data through visual means.

After completing the course, you will be able to create a wide range of visualizations to communicate data insights effectively. You’ll gain the skills to generate static and interactive plots, including 3D visualizations and geographic maps, using Python. Moreover, you will be able to apply these techniques in real-world scenarios, enhancing your ability to present data in a clear, engaging, and actionable way.

To enroll in this course, basic knowledge of Python programming is recommended. Familiarity with Python libraries such as NumPy and Pandas will be helpful, as these are often used to manipulate data before visualization. No advanced math or statistics background is necessary, but understanding how data is structured will enhance your learning experience.

This course is for anyone interested in data science, analytics, or any field where data visualization is important. It is particularly useful for individuals who wish to present data effectively to an audience or use visuals to explore and communicate insights. Whether you're a beginner or have some experience with Python, this course is designed to provide you with the skills needed to make professional-grade data visualizations.