A data visualization curriculum of interactive notebooks.

Overview

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.

Comments
  • Build a Jupyter book

    Build a Jupyter book

    @domoritz Here is the Jupyter Book PR. I moved the notebooks to the doc folder and added CI to rebuild the book upon changes to this folder. You can have a peak at the rendered book from my branch here. I used the logo from your github organization for the book and a slightly modified version of the readme for the landing page (but please edit if this is not appropriate).

    close #13

    opened by joelostblom 9
  • Add Nextjournal notebooks

    Add Nextjournal notebooks

    Hi, I took the freedom to add those great Notebooks to Nextjournal! It has a nice way to publish notebooks and remembers all installed software, so all notebooks "just run" ;) If you already have an account, I can also transfer the ownership of those notebooks to you!

    Best, Simon

    opened by SimonDanisch 8
  • Chart sizing wrong in Nextjournal

    Chart sizing wrong in Nextjournal

    For example, see: https://github.nextjournal.com/uwdata/visualization-curriculum/blob/master/altair_interaction.ipynb

    Some of the chart views in the notebook are not properly sized (widgets are below the fold, or even whole charts are not properly captured). This may be a Nextjournal issue; don't know if there is something we can do on our end to fix this.

    @domoritz any ideas? I haven't used Nextjournal before and I think you merged these additions?

    opened by jheer 7
  • Permission to remix the material from this repo into our univeristy course

    Permission to remix the material from this repo into our univeristy course

    Hello! We would like to remix much of the material from this repo into one of our university courses (with accreditation of course) and I just wanted to double check if this is OK. The remixing will mostly entail reordering to fit with our curriculum and extending the material where we see fit. I saw that the license is BSD-3 for the repo, but just wanted to double check before going ahead with this.

    opened by joelostblom 4
  • replace rangeStep with `chart.properties(width={

    replace rangeStep with `chart.properties(width={"step": rangeStep})`

    Per the latest release notes

    image

    The current use of rangeStep is causing an error for people trying to run this notebook with the latest version of Altair. I tried to make the most minimal change possible to the notebook so that the diffs are human-readable. 🙇 Thank you so much for this very useful tutorial.

    cc/: @dansbecker

    opened by hamelsmu 4
  • [Altair-Intro] `alt.renderers.enable('jupyterlab')` is not a part of renderer discussion

    [Altair-Intro] `alt.renderers.enable('jupyterlab')` is not a part of renderer discussion

    In https://github.com/uwdata/visualization-curriculum/blob/master/altair_introduction.ipynb, there is a section about renderers on the top of the page:

    image

    Yet, alt.renderers.enable('jupyterlab') call is actually happening when we call chart the first time.

    image

    opened by kanitw 3
  • Width 'step' does not work

    Width 'step' does not work

    Great tutorial, very clear and helpful. Thanks!

    https://github.com/uwdata/visualization-curriculum/blob/master/altair_marks_encoding.ipynb

    This code is used a number of times, but does not seem to be valid.

    .properties(
        width={"step": 50} # adjust the step parameter
    )
    

    A numerical value does work: e.g. width=100 I could not find from the documentation how to apply the step

    opened by Juan-132 2
  • Show uwdata: Open Source Blogging Platform w/ GitHub Pages & Native Support For Jupyter and Altair

    Show uwdata: Open Source Blogging Platform w/ GitHub Pages & Native Support For Jupyter and Altair

    @jheer I really loved these tutorials on Altair, as they demystified Altair for me.

    I'm working with Jeremy Howard (@jph00) on fastpages

    The reason we created this is we wanted a blogging system that was easy to use but also open source, and where people could own their data. Plus, we wanted to support cool features like interactive charts & graphs in Altair! A summary of features is below, which can also be viewed on the README:

    image

    Sharing this incase it is interesting for your students, especially to share their cool visualization projects! Thank you 🙇

    opened by hamelsmu 2
  • Broken link for timeunits

    Broken link for timeunits

    The "complete list of time units" link in the "Time Units" section of altair_data_transformation.ipynb is broken.

    Should probably be replaced with: https://altair-viz.github.io/user_guide/transform/timeunit.html#user-guide-timeunit-transform

    opened by ltirrell 1
  • Language guidelines

    Language guidelines

    The University of Washington works hard to foster an inclusive and welcoming culture for everyone in the campus community.

    Unfortunately, looking over your GitHub repositories, I have identified language that can be considered offensive due to its racist origins. Specifically the branch names, but I imagine if I looked at the code itself, I would find more.

    Can you let me know when you’ll be adjusting the settings to be a inclusive product/service and follow University of Washington language guidelines?

    opened by ghost 1
  • Add Nextjournal option, take two

    Add Nextjournal option, take two

    Hi @domoritz! This adds the option to view & run these notebooks in Nextjournal. We made sure all notebooks are runnable as-is now. This supersedes #6.

    opened by mk 1
  • [Multi-View] Consider suggesting people to color axis title for dual axis chart

    [Multi-View] Consider suggesting people to color axis title for dual axis chart

    like in https://vega.github.io/vega-lite/examples/layer_dual_axis.html

    image

    The current example in the notebook doesn't make it clear which variable is which mark

    image

    (It's ok for people who follow the tutorial as they created it themselves, but once they copy this example to create charts and share with other audience, it would be confusing.)

    opened by kanitw 3
Releases(v1.1)
Owner
UW Interactive Data Lab
Visualization + Analysis
UW Interactive Data Lab
Cartopy - a cartographic python library with matplotlib support

Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy. Table of contents Overview Get in touch License an

1.2k Jan 01, 2023
A set of useful perceptually uniform colormaps for plotting scientific data

Colorcet: Collection of perceptually uniform colormaps Build Status Coverage Latest dev release Latest release Docs What is it? Colorcet is a collecti

HoloViz 590 Dec 31, 2022
This project is an Algorithm Visualizer where a user can visualize algorithms like Bubble Sort, Merge Sort, Quick Sort, Selection Sort, Linear Search and Binary Search.

Algo_Visualizer This project is an Algorithm Visualizer where a user can visualize common algorithms like "Bubble Sort", "Merge Sort", "Quick Sort", "

Rahul 4 Feb 07, 2022
Automatization of BoxPlot graph usin Python MatPlotLib and Excel

BoxPlotGraphAutomation Automatization of BoxPlot graph usin Python / Excel. This file is an automation of BoxPlot-Graph using python graph library mat

EricAugustin 1 Feb 07, 2022
Visualization Library

CamViz Overview // Installation // Demos // License Overview CamViz is a visualization library developed by the TRI-ML team with the goal of providing

Toyota Research Institute - Machine Learning 67 Nov 24, 2022
Official Matplotlib cheat sheets

Official Matplotlib cheat sheets

Matplotlib Developers 6.7k Jan 09, 2023
nvitop, an interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

Xuehai Pan 1.3k Jan 02, 2023
Missing data visualization module for Python.

missingno Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities tha

Aleksey Bilogur 3.4k Dec 29, 2022
A Python wrapper of Neighbor Retrieval Visualizer (NeRV)

PyNeRV A Python wrapper of the dimensionality reduction algorithm Neighbor Retrieval Visualizer (NeRV) Compile Set up the paths in Makefile then make.

2 Aug 29, 2021
A package for plotting maps in R with ggplot2

Attention! Google has recently changed its API requirements, and ggmap users are now required to register with Google. From a user’s perspective, ther

David Kahle 719 Jan 04, 2023
2D maze path solver visualizer implemented with python

2D maze path solver visualizer implemented with python

SS 14 Dec 21, 2022
Multi-class confusion matrix library in Python

Table of contents Overview Installation Usage Document Try PyCM in Your Browser Issues & Bug Reports Todo Outputs Dependencies Contribution References

Sepand Haghighi 1.3k Dec 31, 2022
Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.

Numerical methods Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary

Aleksey Korshuk 5 Apr 29, 2022
I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things

Genuary 2022 I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things. Every day there is a new prompt for making

Joaquín Feltes 1 Jan 10, 2022
Decision Border Visualizer for Classification Algorithms

dbv Decision Border Visualizer for Classification Algorithms Project description A python package for Machine Learning Engineers who want to visualize

Sven Eschlbeck 1 Nov 01, 2021
A python package for animating plots build on matplotlib.

animatplot A python package for making interactive as well as animated plots with matplotlib. Requires Python = 3.5 Matplotlib = 2.2 (because slider

Tyler Makaro 394 Dec 18, 2022
A blender import/export system for Defold

defold-blender-export A Blender export system for the Defold game engine. Setup Notes There are no exhaustive documents for this tool yet. Its just no

David Lannan 27 Dec 30, 2022
Visualizations for machine learning datasets

Introduction The facets project contains two visualizations for understanding and analyzing machine learning datasets: Facets Overview and Facets Dive

PAIR code 7.1k Jan 07, 2023
Plotting library for IPython/Jupyter notebooks

bqplot 2-D plotting library for Project Jupyter Introduction bqplot is a 2-D visualization system for Jupyter, based on the constructs of the Grammar

3.4k Dec 30, 2022
Flame Graphs visualize profiled code

Flame Graphs visualize profiled code

Brendan Gregg 14.1k Jan 03, 2023