uwdata/visualization-curriculum uwdata/visualization-curriculum

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A data visualization curriculum of interactive notebooks.

Data Visualization Curriculum

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.

Curriculum

Table of Contents

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

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

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

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

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

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

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

Support

Getting Started

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

Online

Local Installation

  1. Install Altair and a notebook environment. The most recent versions of these notebooks use Altair version 4.
  2. 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.)
  3. 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.

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.

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