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https://nbdev.fast.ai/tutorials/best_practices.html

https://pandoc.org/MANUAL.html#pandocs-markdown

https://quarto.org/docs/authoring/markdown-basics.html#tables

https://quarto.org/docs/authoring/callouts.html

Table of Contents

Motiviation


Sample Image

I want to create interactive ipynb visualizations that persists when converted to html (without the use of using iframes). Jupyter Notebooks being a web app makes this possible as Ipynb's cell outputs are actually just IFRAMES. Jupyter notebooks run a web server responsible for routing communication from your browser to your local machine which means interactive visualizations are just a javascript script away.

Background

https://bniajfi.org/wp-content/themes/Grido/Theme_v1_3/js/bnia.js https://bniajfi.org/guidepost/communityAdjacents.json

https://bniajfi.org/guidepost/vega_renderer.js https://bniajfi.org/guidepost/custom_plotly_renderers.js

https://bniajfi.org/guidepost/map_handler.js https://bniajfi.org/guidepost/script_vars_events.js https://bniajfi.org/guidepost/script.js

https://github.com/nicolaskruchten/pivottable/wiki/Parameters#options-object-for-pivotui

https://pivottable.js.org/dist/pivot.js

How to Use

Perform typical python data science operations

Methods:

  1. Display the data interactively.

A new visual is created each time unless you use a referenced id.

  1. Update the referenced table to display a specific column, row, and visualization type

test