This course covers the important aspects of building visualizations in Pygal, using styles and configurations to govern chart behavior, rendering and exporting to SVG and other specialized formats, and serving Pygal visualizations in web content.
Vector image formats such as SVG possess many important advantages over scalar formats such as PNG and JPEG. Using SVG, you can build high-quality, compact visualizations that render on low-resolution devices and that can be scaled, zoomed, and moved without distortion.
Read more
This course covers the important aspects of building visualizations in Pygal, using styles and configurations to govern chart behavior, rendering and exporting to SVG and other specialized formats, and serving Pygal visualizations in web content.
Vector image formats such as SVG possess many important advantages over scalar formats such as PNG and JPEG. Using SVG, you can build high-quality, compact visualizations that render on low-resolution devices and that can be scaled, zoomed, and moved without distortion.
This course covers the important aspects of building visualizations in Pygal, using styles and configurations to govern chart behavior, rendering and exporting to SVG and other specialized formats, and serving Pygal visualizations in web content.
Vector image formats such as SVG possess many important advantages over scalar formats such as PNG and JPEG. Using SVG, you can build high-quality, compact visualizations that render on low-resolution devices and that can be scaled, zoomed, and moved without distortion.
In this course, Pygal: Python Data Playbook, you will gain the ability to construct an array of visualizations and render them to SVG format using Pygal.
First, you will learn the advantages of working with Pygal for building SVGs and understand the niche that Pygal occupies relative to other visualization packages such as Matplotlib, Seaborn, Bokeh, and Plotly. Next, you will discover how to build an array of visualizations in Pygal, from in-memory as well as file data. You will then construct a visualization including simple charts such as Line, Tree, and Bar graphs, as well as specialized types like TreeMaps and Sparklines. You will understand the different types of Styles and Configurations that can be used to govern chart appearance. You will work with built-in, parametric, and custom styles, as well as Chart, Serie, and Value configurations.
Finally, you will explore how to render Pygal visualizations to a range of image and non-image formats, including XML element trees and base64 encoded formats for online transfer. You will round out the course by building a web application using the Flask microframework in order to render and serve Pygal charts.
When you are finished with this course, you will have the skills and knowledge of building and rendering visualizations in Pygal needed to effectively harness the many advantages of the Scalable Vector Graphics format.
What's inside
Syllabus
Course Overview
Getting Data into Pygal
Plotting Basic Pygal Charts
Visualizing Complex Data with Advanced Charts
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Syllabus
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Activities
Review prerequisite data visualization concepts
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This review will refresh your knowledge of basic data visualization concepts and ensure you start the course on a solid footing.
Show steps
-
Revisit key concepts, such as data types, scales, and chart types
-
Review examples and tutorials to ensure understanding
Follow tutorials to enhance your Pygal skills
Show steps
Guided tutorials will provide structured guidance and examples to complement your learning.
Show steps
-
Identify tutorials covering advanced Pygal techniques or specific chart types
-
Follow the tutorials and implement the techniques in your own visualizations
Attend peer study sessions to discuss and troubleshoot
Show steps
Engaging with peers will foster collaboration, provide new perspectives, and enhance your understanding.
Show steps
-
Join or start a study group with other course participants
-
Schedule regular meetings to discuss course topics, share knowledge, and troubleshoot
Four other activities
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Create visualizations for real-world data sets
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Hands-on practice will solidify your understanding of Pygal's functionalities and improve your data visualization skills.
Show steps
-
Source real-world data sets (e.g., Kaggle, government websites)
-
Create visualizations using Pygal to explore and present the data
Document your learning journey with a blog post
Show steps
Documenting your learning process will help you synthesize and retain the course material.
Show steps
-
Choose a topic related to a specific Pygal feature or technique you learned
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Write a blog post explaining the concept and providing examples
-
Share your post online or with classmates for feedback
Create a data visualization dashboard using Pygal
Show steps
A project will challenge your skills, reinforce your learning, and showcase your proficiency in data visualization with Pygal.
Show steps
-
Define the purpose and scope of your dashboard
-
Gather and prepare the necessary data
-
Design and implement the dashboard using Pygal
-
Deploy and share your dashboard
Build a web application to display interactive Pygal visualizations
Show steps
Creating a web application will extend your skills to integrate Pygal with web development frameworks.
Show steps
-
Learn the basics of a web development framework such as Flask
-
Integrate Pygal into your web application
-
Create interactive visualizations that respond to user input
-
Deploy your web application
Review prerequisite data visualization concepts
Show steps
This review will refresh your knowledge of basic data visualization concepts and ensure you start the course on a solid footing.
Show steps
- Revisit key concepts, such as data types, scales, and chart types
- Review examples and tutorials to ensure understanding
Follow tutorials to enhance your Pygal skills
Show steps
Guided tutorials will provide structured guidance and examples to complement your learning.
Show steps
- Identify tutorials covering advanced Pygal techniques or specific chart types
- Follow the tutorials and implement the techniques in your own visualizations
Attend peer study sessions to discuss and troubleshoot
Show steps
Engaging with peers will foster collaboration, provide new perspectives, and enhance your understanding.
Show steps
- Join or start a study group with other course participants
- Schedule regular meetings to discuss course topics, share knowledge, and troubleshoot
Create visualizations for real-world data sets
Show steps
Hands-on practice will solidify your understanding of Pygal's functionalities and improve your data visualization skills.
Show steps
- Source real-world data sets (e.g., Kaggle, government websites)
- Create visualizations using Pygal to explore and present the data
Document your learning journey with a blog post
Show steps
Documenting your learning process will help you synthesize and retain the course material.
Show steps
- Choose a topic related to a specific Pygal feature or technique you learned
- Write a blog post explaining the concept and providing examples
- Share your post online or with classmates for feedback
Create a data visualization dashboard using Pygal
Show steps
A project will challenge your skills, reinforce your learning, and showcase your proficiency in data visualization with Pygal.
Show steps
- Define the purpose and scope of your dashboard
- Gather and prepare the necessary data
- Design and implement the dashboard using Pygal
- Deploy and share your dashboard
Build a web application to display interactive Pygal visualizations
Show steps
Creating a web application will extend your skills to integrate Pygal with web development frameworks.
Show steps
- Learn the basics of a web development framework such as Flask
- Integrate Pygal into your web application
- Create interactive visualizations that respond to user input
- Deploy your web application
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