To The Web and Beyond

on YouTube ↗34m

" summary

Claim: the most practical dataviz stack is Python for cleaning and serving and JavaScript for interactive rendering. Concrete tools and steps include using Python Eve + MongoDB and four config files to deploy an API to Heroku, serving JSON (example: Nobel winners) to a browser that runs d3; a small label-collision hack fixes overlapping text and the demo works interactively. Notes: Jupyter and plotly/vega are useful but limited, and there are ~11,000 live d3 examples on Block Builder/jsfiddle.

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" chapters (16)

1. 0:00Introduction
2. 1:11Virtual reality and modern languages
3. 2:35Async patterns in JS and Python
4. 4:03Web communication and distribution
5. 6:11Overcoming JS prejudice in Python
6. 8:40JavaScript’s past flaws and modern improvements
7. 11:27Python excels in data processing
8. 12:52Python and JavaScript toolchain for data visualization
9. 15:45Transpiling Python to JS drawbacks
10. 17:16Direct JS control for empowerment
11. 19:27Microsoft’s browser data tools
12. 20:29Vanilla JS for data viz
13. 22:21Efficient data delivery to browser
14. 23:50Cloud API with Python Eve
15. 26:42Conclusion on Python and JavaScript for data visualization
16. 28:06Q&A

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