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Data Science in the Browser with Iodide

Galuh Sahid
November 03, 2019

Data Science in the Browser with Iodide

Mozilla Tech Speakers Meetup - Singapore

Galuh Sahid

November 03, 2019
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  1. !

  2. ! "

  3. https://hal.archives-ouvertes.fr/hal-01676633/document “Many analysts simply choose to explain and share their

    analyses using other, more established media, and provide a link, for the “curious”, to the notebook where they performed the analysis in the first place.” Adam Rule, Aurélien Tabard, James Hollan. Exploration and Explanation in Computational Note- books. ACM CHI Conference on Human Factors in Computing Systems, Apr 2018, Montréal, Canada. pp.1-12, 10.1145/3173574.3173606 . hal-01676633
  4. !

  5. & Hey, can I have that analysis you did yesterday?

    Sure, here is the link. ' & I added some variables that I thought could be useful & the result is better, but could you please help check? This is my link. Yup. No problem, on it. ' Seems like everything is OK! Thanks a lot, this is an awesome work! ' Easy to share & remix
  6. Bringing data science to the browser unlocks a lot of

    ✨ superpowers ✨ • DOM • WebGL • Canvas • WebVR
  7. Use your favorite Python packages • numpy • pandas •

    scikit-learn • nltk • networkx • Complete list: https://github.com/iodide-project/pyodide/tree/ master/packages
  8. Python+JS? Now with even more ✨ superpowers ✨ • Workflows

    that make use of the best of both worlds! Data processing with Python Interactive data visualization with d3.js Example: visualizing complex fraud rings with interactive graph networks
  9. • Workflows that make use of the best of both

    worlds! Data processing with Python Interactive data visualization with d3.js Example: visualizing complex fraud rings with interactive graph networks • Access browser APIs straight from Python! Manipulate DOM without touching JavaScript Python+JS? Now with even more ✨ superpowers ✨
  10. Data science communication matters • Influences how people make decisions

    • We have to make sure that our work is: - Transparent - Reproducible
  11. There are a lot more things to do “We envision

    a future workflow that allows you to do your data munging in Python, fit a quick model in R or JAGS, solve some differential equations in Julia, and then display your results with a live interactive d3+JavaScript visualization... and all that within within a single, portable, sharable, and hackable file.” https://github.com/iodide-project/iodide Contribute to Iodide @ GitHub
  12. References • Iodide @ Mozilla Hacks • Pyodide @ Mozilla

    Hacks • https://alpha.iodide.io/ • Iodide @ GitHub