Interactive Data Visualization
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Description
This open educational resource (OER) is intended as the basis for an undergraduate course (14 week) where the students have already been exposed to at least one semester of a high-level programming language such as Python. The intended student does not have to be familiar with web programming standards: HTML, CSS and JavaScript since we review those aspects initially. We present the material as a series of jupyter notebooks intended to be run by the student using a standard python3 kernel attached to a scientific python distribution such as Anaconda. These notebooks contain cells which are markup (which is compatible with HTML5) or code (in one of the supported programming languages such as python). When hosted on a platform like google collaborate, they allow the user to view the text, click on hyperlinks and also run some of the python code examples that illustrate the visualization and machine learning methods. If using a platform such as GitHub, the rendered jupyter notebooks will not have a running kernel attached and will therefore not execute python code. The foundational components for practice will be client-side web applications consisting of a folder which HTML, CSS, JS and data files inside (such as CSV and JSON formats). We include appendix sections that have some details in setting up a development environment and for hosting a finished visualization on github.io.
This work is published under a GPL-3.0 license. Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
Publication Date
2025
Keywords
OER, data visualization, computer science
Recommended Citation
Becker, Timothy James, "Interactive Data Visualization" (2025). Open Educational Resources. 7.
https://digitalcommons.conncoll.edu/oer/7