Learning pathway
Using Jupyter Notebooks for biomolecular research
- Overview
- About this pathway
- An overview of Jupyter Notebooks
- Code cells
- Markdown cells
- Raw cells
- Good practice and example usage of Jupyter Notebooks
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Code cells
Code cells are the workhorses of the Jupyter Notebook. IPython (Interactive Python) is a project related to the Jupyter project and provides the default python kernel. Depending on the programming language(s) that you use, choose between the following options:
- Jupyter Notebooks with IPython
- Installing other kernels in your notebook
IPython: beyond plain Python
An interactive IPython introduction with tutorials and examples showcasing the features specific to IPython.
After this course you should be able to:
- Run code cells in a Jupyter Notebook
- Get object details and other help within the notebook
- Use iPython magic functions
- Include plots within your notebook
- Change how errors in python code are displayed within the notebook
- Know which rich output representations can be declared by an object
- The difference between embedded and non-embedded images and how to include these in a notebook
- How rich output is affected by the IPython security model
IPython: beyond plain Python
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More information about this resourceJupyter Notebooks: Multiple Languages, Frontends
The section of the Jupyter documentation explaining how kernels work and how to install other programming languages in your notebook.
After this course you should:
- Know how the Jupyter Notebook frontend works
- Know the difference between wrapper and native kernels and know the kernel process
- Be able to install a different programming language in your notebook
- Know where to find community-maintained kernels