A data visualization curriculum of interactive notebooks.
A data visualization curriculum of interactive notebooks, using Vega-Lite and Altair. This repository contains a series of Python-based Jupyter notebooks. The notebooks are online in a Jupyter book, runnable locally or online on Colab, Nextjournal, or Deepnote. A corresponding set of JavaScript notebooks are available online on Observable.
Introduction to Vega-Lite / Altair
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Data Types, Graphical Marks, and Visual Encoding Channels
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Data Transformation
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Scales, Axes, and Legends
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Multi-View Composition
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Interaction
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
Cartographic Visualization
Jupyter Book |
Jupyter |
Colab |
Nextjournal |
Observable |
Deepnote
The visualization curriculum can be used either online or on your local computer.
jupyter lab
within the directory containing the notebooks.Depending on your programming environment (and whether or not you have a live internet connection), you may want to specify a particular renderer for Altair.
Developed at the University of Washington by Jeffrey Heer, Dominik Moritz, Jake VanderPlas, and Brock Craft. Thanks to the UW Interactive Data Lab and Arvind Satyanarayan for their valuable input and feedback! Thanks also to the students of UW CSE512 Spring 2019, the first group to use these notebooks within an integrated course curriculum.