Lunch bytes #2: Jupyter Notebooks - pros and cons

7 October 2020 - 12:00-13:00
Google meet
Fedor Gorokhovik, John Charlton, Richard Darst, University of Sheffield

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LunchBytes is a new monthly series of short talks for those in the research community at TUOS who work with/write code, use/manage research data and use/manage research infrastructure. We hope through these talks we will come together as a community to discuss best practices and useful methods/tools.

Notebooks (Jupyter, R etc) have become a popular tools for research and prototyping in data science, but what are the advantages and pitfalls? At this LunchBytes event we’ll be exploring Jupyter notebooks and their pros and cons via three short talks. Each will be ~10 minutes, leaving half an hour for discussion/questions.

Joining instructions

This lunchBytes session will be run at the following Google meet ( which is open to members of the University of Sheffield. If you would like to attend and do not have a Sheffield account, please contact the organisers by email at

Google JamBoard for Q&A: note down questions/comments (using JamBoard Sticky Notes) before/during the event.

Materials presented


(Mis)uses of notebooks as production tools in the financial industry

Fedor Gorokhovik, Man group

This short presentation aims at introducing how Jupyter became one of the main tools in the financial industry, slowly replacing Excel. Why is it the perfect tool for the trade, and what are the risks?

Making the most out of notebooks

John Charlton, Sheffield RSE Team

How to use extensions and libraries with Jupyter Notebooks to tackle some of its shortcomings and support the strengths.

Pitfalls of Jupyter notebooks

Richard Darst, Aalto Scientific Computing, Aalto University

Jupyter Notebooks are a great tool for research, data science type things, and teaching. But they are not perfect - they support exploration, but not other parts of the coding phase such as modularity and scaling. This talk lists some common limitations and pitfalls and what you can do to avoid them.

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