- Talk title: A small introduction to Jupyter Notebooks
- Presenter: Florian Ellsäßer [email protected]
- 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
- 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.
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Jupyter Notbooks are a combination of code and explanatory text.
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It can process code of 12 different programming languages
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Key Advantage: A notebook contains both code and its output.
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A notebook is therefore human readable and executable
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Jupyter Notebooks are a great way to communicate scientific analysis
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They are also great for developing code and doing stepwise data analysis because the cell structure facilitates running small code sections
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You can write text in markdown
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You can link to external source
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It runs in your browser (creates local server)
- 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
- Transformation and cleaning of data
- Data visualisation
- Statistical modelling