Oreilly – Python Data Visualization: Create impactful visuals, animations and dashboards 2025-2

Apr 18, 2025 - 19:02

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Python Data Visualization Course: Create impactful visuals, animations and dashboards. This comprehensive course teaches you how to create engaging and impactful visuals, animations and dashboards using Python. You’ll learn the fundamentals of data visualization, including color theory, analytical design and chart types. Then, you’ll learn how to use powerful libraries like Pandas, Matplotlib, Seaborn, Bokeh and Plotly to clean data, build charts, create animations and build interactive dashboards.

What you will learn:

Understand the basics of data visualization: Familiarity with color theory, analytical design, and chart types
Data Cleansing and Visualization with Pandas: Using DataFrames, Series, GroupBy, and Pivot Tables to Clean and Prepare Data
Building static and interactive graphs with Matplotlib: Learn how to use the Matplotlib API to build a variety of graphs, add styles, and create maps.
Creating animations with Matplotlib: Using the Matplotlib animation API to create engaging animations
Building Interactive Dashboards with Jupyter Widgets: Using ipywidgets to Create Interactive Controls in the Browser
Data visualization with Seaborn: Introduction to the Seaborn structure and its differences from Matplotlib
Building Interactive Charts with Bokeh: Learn how to build advanced interactive charts with Bokeh
Create 3D Charts and Animations with Plotly: Use Plotly to Create Attractive 3D Charts and Animations

Who is this course suitable for?

This course is suitable for anyone who wants to improve their skills in data visualization with Python. This course will be useful for data analysts, data scientists, developers, and anyone looking to create engaging and impactful visualizations and dashboards.

Course details for Python Data Visualization: Create impactful visuals, animations and dashboards

Publisher: Oreilly
Instructor: Bruno Goncalves
Training level: Beginner to advanced
Training duration: 6 hours and 36 minutes

Course headings

Python Data Visualization: Introduction
Lesson 1: Human Perception
Topics
1.1 Understanding Color Theory
1.2 Overview of Human Vision
1.3 Color Schemes
Lesson 2: Analytical Design
Topics
2.1 Understand the Fundamental Principles of Analytical Design
2.2 Describe the Fundamental Tools of Visualization
2.3 Advantages and Disadvantages of Different Chart Types
Lesson 3: Data Cleaning and Visualization with Pandas
Topics
3.1 DataFrames and Series
3.2 GroupBy and Pivot Tables
3.3 Merge and Join
3.4 The Plot Function
3.5 Demo
3.6 Time Series
3.7 Bar Plot Demo
Lesson 4: Matplotlib
Topics
4.1 Fundamental Components of a matplotlib plot
4.2 Explore the matplotlib API
4.3 Demo
4.4 Stylesheets
4.5 Demo
4.6 Mapping
4.7 Demo
Lesson 5: Matplotlib Animations
Topics
5.1 Matplotlib Animation API
5.2 Func Animation
5.3 Animation Writers
5.4 Demo
Lesson 6: Jupyter Widgets
Topics
6.1 ipywidgets as Interactive Browser Controls
6.2 Simple Widget Use
6.3 Widget Customization
6.4 Demo
Lesson 7: Seaborn
Topics
7.1 Understand the Structure of seaborn
7.2 Understand the Differences with matplotlib
7.3 Explore the Seaborn API
7.4 Demo
Lesson 8: Bokeh
Topics
8.1 Basic Plotting with Bokeh
8.2 Advanced Plotting
8.3 Networks
8.4 Demo
Lesson 9: Plotly
Topics
9.1 Basic Plotly
9.2 3D and Animated Plots
9.3 Demo
Summary
Python Data Visualization: Summary