Data Visualization Curriculum

A data visualization curriculum of interactive notebooks, using Vega-Lite and Altair. This repository contains a series of Python notebooks using Jupyter and marimo. The notebooks are online in a Jupyter book, runnable locally or online on Colab, Nextjournal, Deepnote, or molab. A corresponding set of JavaScript notebooks are available online on Observable.

Curriculum

Table of Contents

1. Introduction to Vega-Lite / Altair
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

2. Data Types, Graphical Marks, and Visual Encoding Channels
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

3. Data Transformation
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

4. Scales, Axes, and Legends
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

5. Multi-View Composition
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

6. Interaction
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

7. Cartographic Visualization
   Jupyter Book | Jupyter | Colab | Nextjournal | Observable | Deepnote | Marimo

Support

• Altair Debugging Guide
  Jupyter Book | Jupyter | Colab | Nextjournal | Deepnote | Marimo

Getting Started

The visualization curriculum can be used either online or on your local computer.

Online

• Jupyter Book to read Python notebooks online.
• Run the Python notebooks online on Colab, Nextjournal, or Deepnote.
• Run the JavaScript notebooks online using Observable.
• Run the marimo notebooks online using molab.

Local Installation

1. Install Altair and a notebook environment. The most recent versions of these notebooks use Altair version 6.
2. Download the notebooks from the releases page. Typically you will want to use the most recent release.
3. If you are using Jupyter, open the .ipynb 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. With uv, you can run uv run jupyter lab (it automatically installs the dependencies).
4. If you are using marimo, open the .py notebooks in the marimo directory using either marimo run marimo/notebook.py (to use the virtual environment you set up) or uv run marimo run marimo/notebook.py (to automatically install the dependencies in the notebook header).

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.

Publishing the Jupyter Book

The book is built with Jupyter Book 2 and published to GitHub Pages automatically on every push to main via GitHub Actions.

To preview the book locally:

uv run jupyter-book start

To publish manually:

uv run jupyter-book build --html
npx -y gh-pages -n -d _build/html

To execute notebooks during the build, add the --execute flag:

uv run jupyter-book build --execute --html

Credits

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.