Why Jupyter is data scientists’ computational notebook of choice

Re:Why Jupyter is data scientists’ computational notebook of... by bitL on Tuesday October 30, 2018 @11:34AM (#18337586)

You don't use Jupyter notebooks in production; they are super useful for pitching ideas to clients/bosses and doing some early prototyping. I feel sorry for anyone that has to work with "pure data scientists" that have no clue about software engineering practices...

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Re:Why Jupyter is data scientists’ computational notebook of... by brylie on Tuesday October 30, 2018 @12:48PM (#18338651)

FWIW, Netflix uses Jupyter notebooks in production, using nteract UI:

https://medium.com/netflix-techblog/notebook-innovation-591e...

https://nteract.io/

This approach seems promising, particularly as it facilitates cross-disciplinary collaboration.

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Re:Why Jupyter is data scientists’ computational notebook of... by cwyers on Tuesday October 30, 2018 @12:46PM (#18338618)

It depends on what you're doing, yeah? In RMarkdown notebooks... yeah, I wouldn't write models in one. But if the focus is on embedding some visualizations and tables into a document, and then refreshing the document to every so often pull in new data, I can see that as a production use for a notebook. TL;DR: Can be useful for reporting, wouldn't use it anywhere else in the pipeline.

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