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
A Python toolbox for gaining geometric insights into high-dimensional data

"To deal with hyper-planes in a 14 dimensional space, visualize a 3D space and say 'fourteen' very loudly. Everyone does it." - Geoff Hinton Overview

Contextual Dynamics Laboratory 1.8k Dec 29, 2022
Show Data: Show your dataset in web browser!

Show Data is to generate html tables for large scale image dataset, especially for the dataset in remote server. It provides some useful commond line tools and fully customizeble API reference to gen

Dechao Meng 83 Nov 26, 2022
High performance, editable, stylable datagrids in jupyter and jupyterlab

An ipywidgets wrapper of regular-table for Jupyter. Examples Two Billion Rows Notebook Click Events Notebook Edit Events Notebook Styling Notebook Pan

J.P. Morgan Chase 75 Dec 15, 2022
Python package to visualize and cluster partial dependence.

partial_dependence A python library for plotting partial dependence patterns of machine learning classifiers. The technique is a black box approach to

NYU Visualization Lab 25 Nov 14, 2022
Python Data. Leaflet.js Maps.

folium Python Data, Leaflet.js Maps folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js

6k Jan 02, 2023
Sentiment Analysis application created with Python and Dash, hosted at socialsentiment.net

Social Sentiment Dash Application Live-streaming sentiment analysis application created with Python and Dash, hosted at SocialSentiment.net. Dash Tuto

Harrison 456 Dec 25, 2022
GDSHelpers is an open-source package for automatized pattern generation for nano-structuring.

GDSHelpers GDSHelpers in an open-source package for automatized pattern generation for nano-structuring. It allows exporting the pattern in the GDSII-

Helge Gehring 76 Dec 16, 2022
nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.

nptsne nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling. For more detail s

Biomedical Visual Analytics Unit LUMC - TU Delft 29 Jul 05, 2022
A tool for creating SVG timelines from simple JSON input.

A tool for creating SVG timelines from simple JSON input.

Jason Reisman 432 Dec 30, 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
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda

Alex Riley 1.9k Jan 08, 2023
Turn a STAC catalog into a dask-based xarray

StackSTAC Turn a list of STAC items into a 4D xarray DataArray (dims: time, band, y, x), including reprojection to a common grid. The array is a lazy

Gabe Joseph 148 Dec 19, 2022
This is a Boids Simulation, written in Python with Pygame.

PyNBoids A Python Boids Simulation This is a Boids simulation, written in Python3, with Pygame2 and NumPy. To use: Save the pynboids_sp.py file (and n

Nik 17 Dec 18, 2022
a simple REPL display lib for circuitpython

Circuitpython-termio-lib a simple REPL display lib for circuitpython Fonctions cls clear terminal screen and set cursor on top left : coords 0,0 usage

BeBoXoS 1 Nov 17, 2021
FURY - A software library for scientific visualization in Python

Free Unified Rendering in Python A software library for scientific visualization in Python. General Information • Key Features • Installation • How to

169 Dec 21, 2022
Visualize your pandas data with one-line code

PandasEcharts 简介 基于pandas和pyecharts的可视化工具 安装 pip 安装 $ pip install pandasecharts 源码安装 $ git clone https://github.com/gamersover/pandasecharts $ cd pand

陈华杰 2 Apr 13, 2022
Matplotlib JOTA style for making figures

Matplotlib JOTA style for making figures This repo has Matplotlib JOTA style to format plots and figures for publications and presentation.

JOTA JORNALISMO 2 May 05, 2022
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph

TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the comput

Eric Jang 1.4k Dec 15, 2022
basemap - Plot on map projections (with coastlines and political boundaries) using matplotlib.

Basemap Plot on map projections (with coastlines and political boundaries) using matplotlib. ⚠️ Warning: this package is being deprecated in favour of

Matplotlib Developers 706 Dec 28, 2022
Matplotlib colormaps from the yt project !

cmyt Matplotlib colormaps from the yt project ! Colormaps overview The following colormaps, as well as their respective reversed (*_r) versions are av

The yt project 5 Sep 16, 2022