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Course Description

Users often demand rich, interactive data visualizations they can ask their own questions to, but the tools to create them are often proprietary or outside the normal tool chain of a data professional; fundamentally, interactive visualizations are best implemented and deployed using web technologies. In this class, we will introduce two open-source options for constructing custom, web-interactive visualizations. Altair is a python library, but its output is in a grammar that can be converted to web-based visualizations, so Python users will be familiar with its syntax. D3.js is a powerful and popular JavaScript library for creating data driven web pages, and though it requires more knowledge of web technologies such as HTML and Javascript, the possibilities regarding custom visualizations with it are endless. In this class, both libraries will be used to construct custom data visualizations for different use cases.

 

Enrollment in this course is open to all students and applies credit toward the

  • Visual Analytics track.

Course Objectives

Upon successful completion of the course, students will:

  • Understand the D3 plugin system to abstract common visualizations.

  • Weigh deployment options for visual analytics based on use case.

  • Evaluate visualization libraries across languages by interpretability value vs implementation complexity.

  • Implement data-driven web pages using D3.js 

  • Implement and embed visualizations in web pages using Altair and vegaEmbed.

Notes

Enrollment in this course is open to all students and applies CEUs towards the Visual Analytics track.

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