Pygal 2: Python Data Playbook from Pluralsight

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

Rendering Out Charts

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps learners develop skills in graphic design and data analysis, which are highly relevant in industry

Emphasizes building high-quality, compact visualizations that are highly relevant to industry needs

Provides a comprehensive overview of Pygal's features, including styles, configurations, and rendering options

Taught by Kishan Iyer, an experienced instructor in data visualization and analytics

Covers a range of visualization types, from basic charts to advanced visualizations like TreeMaps and Sparklines

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Pygal 2: Python Data Playbook with these 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.

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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

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Guided tutorials will provide structured guidance and examples to complement your learning.

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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

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Engaging with peers will foster collaboration, provide new perspectives, and enhance your understanding.

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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.

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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

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Documenting your learning process will help you synthesize and retain the course material.

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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

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A project will challenge your skills, reinforce your learning, and showcase your proficiency in data visualization with Pygal.

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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

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Creating a web application will extend your skills to integrate Pygal with web development frameworks.

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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

Career center

Learners who complete Pygal 2: Python Data Playbook will develop knowledge and skills that may be useful to these careers:

UX Designer

UX Designers aim to improve the experience that users have interacting with a product. This course can be particularly useful for UX Designers who want to leverage Pygal to create SVG visualizations that are not only informative and useful, but also aesthetically pleasing and scalable.

See salaries and explore the career path for UX Designer

Web Developer

Web Developers create and maintain websites. Pygal is a useful tool for building SVG visualizations that can be rendered in a web browser. This makes Pygal a convenient option for Web Developers who need to create reusable, portable, and interactive visualizations for their web applications.

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Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to analyze large amounts of data. Pygal can help Data Scientists create SVG visualizations of complex datasets in an easy and convenient manner. By leveraging Pygal, Data Scientists can transform complex data into impactful and comprehensible visualizations that aid decision-making.

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Data Analyst

Data Analysts collect, clean, and analyze data to provide meaningful insights to businesses and organizations. This course is very useful for Data Analysts as it focuses on building SVG visualizations in Pygal. Pygal visualizations are particularly useful for presenting data in a clear and concise manner.

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Software Engineer

Software Engineers develop, test, and maintain software systems. Pygal is a useful tool for building SVG visualizations which can be very useful for Software Engineers who want to monitor software performance and behavior, or who need to create visualizations for documentation purposes.

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Quantitative Analyst

Quantitative Analysts (also known as Quants) use mathematical and statistical techniques to analyze financial data. Pygal can be useful for Quants who want an easy and effective way to visualize complex financial data as SVG visualizations.

See salaries and explore the career path for Quantitative Analyst

User Experience Researcher

User Experience Researchers study how users interact with products and services. This course is particularly useful for User Experience Researchers as it helps build a foundation in Pygal, which is a tool that can be used to create SVG visualizations for user testing and feedback.

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Product Manager

Product Managers oversee the development of products and services. Pygal can aid Product Managers by enabling them to create SVG visualizations that showcase product data and insights for stakeholders and team members.

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Business Analyst

Business Analysts use data analysis and modeling techniques to provide insights to businesses. Pygal can help Business Analysts create SVG visualizations to communicate data-driven findings to stakeholders and decision-makers.

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Visual Designer

Visual Designers create visual concepts for products, services, and experiences. This course can be helpful for Visual Designers who want to leverage Pygal's capabilities to create SVG visualizations that are visually appealing and effectively convey data insights.

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Information Designer

Information Designers present data and information in a clear and concise manner. This course can be useful for Information Designers as it helps build a foundation in creating SVG visualizations with Pygal.

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Market Researcher

Market Researchers conduct research to understand market trends and consumer behavior. Pygal may be useful for Market Researchers who want to create SVG visualizations of research data.

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Data Visualization Engineer

Data Visualization Engineers design and develop data visualization solutions. Pygal can be a useful tool for Data Visualization Engineers who want to create SVG visualizations that are both informative and engaging.

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Information Architect

Information Architects design and organize information systems. Pygal can be helpful for Information Architects who want to create SVG visualizations that help users navigate and understand complex information.

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Statistician

Statisticians collect, analyze, and interpret data. Pygal can help Statisticians create SVG visualizations of statistical data in an easy and convenient manner.

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