Topic Jupyter Notebooks

• Talk title: A small introduction to Jupyter Notebooks
• Presenter: Florian Ellsäßer Florian.Ellsaesser@zeu.uni-giessen.de
• Date: 22 June 2022
• Notes by: Christian Krippes and Florian Ellsäßer
• License: CC0 1.0 Universal, see https://creativecommons.org/publicdomain/zero/1.0/
• The talk is available as Jupyter Notebook. You find it in our GitHub Repository
• The example dataset (Iris dataset) is also available in our Repository

Download and Install

• A intallation guide can be found on the Juypter-Website
• The presentation on Jupyter Notebooks (also created in a Jupyter Notebook) can be viewed here.
• An example Jupyter Notebook featuring the famous iris data set can be found here.

What are Jupyter Notebooks

• Jupyter Notbooks are a combination of code and explanatory text.
• It can process code of 12 different programming languages
• Key Advantage: A notebook contains both code and its output.
• A notebook is therefore human readable and executable
• Jupyter Notebooks are a great way to communicate scientific analysis

• They are also great for developing code and doing stepwise data analysis because the cell structure facilitates running small code sections

• You can write text in markdown
• You can link to external source
• It runs in your browser (creates local server)

Use cases

• Documenting a process
• Tutorials e.g. in teaching scientific analysis
• Show how things are used
• Enables learners to try things out
• Data analysis
• Code development
• Create figures

Tasks you can solve with Jupyter Notebooks are

• Transformation and cleaning of data
• Data visualisation
• Statistical modelling