Jupiter notebooks have transformed the way many developers and data scientists do their jobs.

They offer a platform to not just explore, but to explain data and computation.

But how are they really being used?

Adam Ruhl is here to describe his research and PhD dissertation,

which analyzed over one million Jupiter notebooks found out in the wild.

This is Talk Pythonomy.

Episode 171 recorded July 6th, 2018.

Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter where I'm at M. Kennedy.

Keep up with the show and listen to past episodes at TalkPython.fm, and follow the show on Twitter via at talk python.

This episode is brought to you by Linode and Studio 3T. Please check out what they're offering during their segments. It really helps support the show. Adam, welcome to Talk Python. Yeah, I'm great to be

with you. Thanks for inviting me on the show. Yeah, it's great to have you here. I'm really glad

our mutual friend, Philip Quote, introduced us and suggested this show. Yeah, no, you've had a lot of

great people on the show. I mean, Philip included, who I think has been a repeat on the show, which is

great, but other folks in kind of my area of data analysis or computational notebooks,

Min and Matthias from Project Jupiter and DJ Patel,

one of the kind of God bothers in data analysis.

So it's honor to be on here with you today.

It's great to have you.

And that was great to have those people as well.

So we're going to talk about Jupiter notebooks in a super meta way., I've had Matiasan to talk about notebooks as a technology, but we're going to talk about more like how people work with notebooks and how it affects researchers and data science and stuff.

Before we get to that, let's start with your story.

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