jsxgraph VS vizzu-story-js

https://github.com/jsxgraph/jsxgraph

Shoutout to Prof. Wassermann for keeping up the good work.

JSXGraph was part of the European Erasmus+ program ITEMS (https://itemspro.eu). Aim of that project (and related projects where JSXGraph is / was included) is to research on "digital learning" in STEM subjects. The technical focus was on including JSXGraph in moodle courses with the question types STACK and formulas. For this and for certain mathematical topics, JSXGraph has been adapted through out the project.

JSXGraph has been started as a seminar at the University of Bayreuth in 2007. The list of developers is given in the copyright section of the source code, e.g. https://github.com/jsxgraph/jsxgraph/blob/master/src/jxg.js. After the students have left the University, the core developer team is much smaller. Luckily, meanwhile the user community is increasingly providing improvements and bug fixes.

1. They lacked the opportunity to use these charts to present their findings and control the animation better than just (re)running notebook cells.

2. They had challenges using our generic chart-building engine - they are more acquainted with picking a chart type and using the parameters specific to that type.

So we decided to build a new extension that enables our users to add the charts to slides and thus create interactive, animated presentations they can present right from the notebook. The presentation can be controlled with buttons beneath the charts, keyboard shortcuts (arrows, PgUp, PgDn, Home, End), or a clicker. We also added the capability to export these presentations to HTML to share them with others who don't use notebooks.

Example - scroll to the bottom for the presentation: https://vizzuhq.github.io/ipyvizzu-story/examples/demo/ipyvi....

We tackled the other challenge by introducing chart presets: users can now pick from the 40+ pre-defined chart types. https://ipyvizzu.vizzuhq.com/examples/examples.html#Preset-c...

Everything is released under the Apache 2.0 license and is available for JavaScript developers as an open-source data storytelling solution. Technically, in the Jupyter version, it's the JS lib being called from the notebook with a Python interface - similarly to what Plotly does. More info: https://github.com/vizzuhq/vizzu-ext-js-story & https://lib.vizzuhq.com/latest/

We'd love to know more about how our technology can be put to good use, so if you have any feedback or suggestions, we're here to listen.