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

This course is part of Data Understanding and Data Visualization with Python Specialization

Instructor: Packt - Course Instructors

Included with Coursera Plus

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6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Details to know

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This course is part of the Data Understanding and Data Visualization with Python Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 6 modules in this course

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.

What's included

28 videos2 readings1 assignment1 plugin

28 videosTotal 165 minutes

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

2 readingsTotal 20 minutes

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

1 assignmentTotal 15 minutes

Matplotlib for Data Visualization - Assessment15 minutes

1 pluginTotal 15 minutes

Understanding and Using Matplotlib Style, Labels, and Limits15 minutes

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.

What's included

10 videos1 assignment1 plugin

10 videosTotal 49 minutes

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

1 assignmentTotal 15 minutes

Seaborn for Data Visualization - Assessment15 minutes

1 pluginTotal 15 minutes

Exploring Seaborn for Data Visualization15 minutes

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.

What's included

5 videos1 assignment1 plugin

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.

What's included

6 videos1 assignment1 plugin

6 videosTotal 26 minutes

Plotly 3D Interactive Scatter Plot7 minutes
Plotly 3D Interactive Scatter Plot Quiz1 minute
Plotly 3D Interactive Scatter Plot Solution5 minutes
Plotly 3D Interactive Surface Plot5 minutes
Plotly 3D Interactive Surface Plot Quiz1 minute
Plotly 3D Interactive Surface Plot Solution5 minutes

1 assignmentTotal 15 minutes

Plotly for 3D Interactive Plotting - Assessment15 minutes

1 pluginTotal 15 minutes

Creating and Analyzing 3D Plots with Plotly15 minutes

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.

What's included

3 videos1 assignment1 plugin

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.

What's included

2 videos1 reading3 assignments

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Instructor

Packt - Course Instructors

Packt

986 Courses238,111 learners

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Packt

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Frequently asked questions

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.