Session 8 - Tools: Jupyter Notebook & Python for Data Scientists

Presenter Information/ Coauthors Information

David Zeng, Dakota State University

Presentation Type

Invited

Track

Tools

Abstract

Jupyter is a free, open-source, interactive web browser-based tool known as a computational notebook, which data scientists can use to combine source codes, computational output, explanatory text and multimedia resources in a single document. For data scientists, Jupyter Notebook, combined with Python, has emerged as the de facto standard. As the most popular form of interactive computing, Jupyter notebooks provide an environment in which users execute code, see what happens, modify and repeat in a kind of iterative conversation between the data scientist and data. This introductory presentation demonstrates examples of how Jupyter (with Python) would help data scientists and learners of data analytics. New tools such as JupyterLab and JupyterHub will be introduced as well.

Start Date

2-11-2020 2:30 PM

End Date

2-11-2020 3:25 PM

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Feb 11th, 2:30 PM Feb 11th, 3:25 PM

Session 8 - Tools: Jupyter Notebook & Python for Data Scientists

Pheasant Room 253 A/B

Jupyter is a free, open-source, interactive web browser-based tool known as a computational notebook, which data scientists can use to combine source codes, computational output, explanatory text and multimedia resources in a single document. For data scientists, Jupyter Notebook, combined with Python, has emerged as the de facto standard. As the most popular form of interactive computing, Jupyter notebooks provide an environment in which users execute code, see what happens, modify and repeat in a kind of iterative conversation between the data scientist and data. This introductory presentation demonstrates examples of how Jupyter (with Python) would help data scientists and learners of data analytics. New tools such as JupyterLab and JupyterHub will be introduced as well.