Cool! Here are a few ways to get the interactive visualizations elsewhere (outside of the notebook).
1) You can save them to a standalone, self-contained, html file: See https://community.plot.ly/t/proper-way-to-save-a-plot-to-htm...
2) You can save them to an html <div> element and embed them in another web page: See https://stackoverflow.com/a/38032952/4551895
3) You can upload them to plot.ly and share the link
Re:Introducing plotly.py 3.0.0
by jjoonathan on Thursday July 05, 2018 @04:07PM
(#17466366)
I want to use plotly so badly but I don't want to sink an investment into another sticky commercial ecosystem -- I've had to do that with Mathematica and Matlab, I don't want to do it again. How good/bad is plotly in comparison?
Obviously python itself is open, I mean the API :-)
Actually, you don't need to sink any investment into a commercial ecosystem here!
plotly.py and the plotly.js rendering library are both MIT licensed, developed in the open on GitHub, and totally self-contained.
Everything in the technology stack used in the announcement post is free, open source, self-contained, usable offline, and doesn't require an account. The plot.ly cloud integration is totally optional.
Re:Introducing plotly.py 3.0.0
by jjoonathan on Thursday July 05, 2018 @04:42PM
(#17466661)
Cool! I'll have to give it a look then!
It's completely open and that's amazing. The ability to design plot.ly plots offline in a jupyter notebook and easily deploy it to our reporting website (Using Dash) is so quick and easy. Even the default interactive elements is plenty for most use cases.
I strongly suggested using plotly instead (either this Python API or the R/ggplot2 API) as it saved a lot of headaches. The native Notebook capabilities are very nice too. (the hard part is extracting the interactive visualization to use elsewhere)