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.
This fork publishes the curriculum under https://masteringdata.ai/visualization-curriculum.
-
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
- Altair Debugging Guide
Jupyter Book | Jupyter | Colab | Nextjournal | Deepnote
The visualization curriculum can be used either online or on your local computer.
- Jupyter Book to read Python notebooks online.
- Run the Python notebooks online on Colab, Nextjournal, or Deepnote
- Run the JavaScript notebooks online using Observable
- Install Altair and a notebook environment. The most recent versions of these notebooks use Altair version 4.
- Download the notebooks from the releases page. Typically you will want to use the most recent release. (If you wish to use notebooks for Altair version 3, download the Altair v3.2 release.)
- Open the notebooks in your local notebook environment. For example, if you have JupyterLab installed (v1.0 or higher is required), run
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.