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Data Management Planning: Jupyter notebooks

Information on best practices and standards for data management planning.


The Jupyter Notebook is an interactive computing environment that enables users to author notebook documents that include code, interactive widgets, plots, narrative text, equations, images and even video! The Jupyter name comes from 3 programming languages: Julia, Python, and R. It is a popular tool for literate programming, which refers to interweaving code and natural language together to form a narrative (like an executable paper!).

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The Jupyter Notebook combines three components (from the docs):

  • The notebook web application: An interactive web application for writing and running code interactively and authoring notebook documents.

  • Kernels: Separate processes started by the notebook web application that runs users’ code in a given language (e.g. python, R, Julia, Go, and more -- get the full list of kernels from the wiki) and returns output back to the notebook web application. The kernel also handles things like computations for interactive widgets, tab completion and introspection.

  • Notebook documents: Self-contained documents that contain a representation of all content visible in the notebook web application, including inputs and outputs of the computations, narrative text, equations, images, and rich media representations of objects. Each notebook document has its own kernel.

Put together, Jupyter Notebooks can be used to write 'executable papers' -- some great examples are here:


You can install jupyter notebooks and some key kernels on your computer in a few ways:

Recommended method -- download using Anaconda (make sure you select version 3.*), which gives you jupyter, python 3, and a lot of key python libraries for research: After you've finished downloading + installing with Anaconda, you should see an application "Jupyter notebooks" in your list of applications.

If you're comfortable with the terminal:

python3 -m pip install --upgrade pip
python3 -m pip install jupyter
jupyter notebooks # launches the notebook interface

Jupyter notebooks can be comprised mainly of two types of cells (though more can be added with plugins).

Markdown Cells (for narratives):

Code Cells (for data cleaning, analysis, visualization, etc.):

  • Executable code in a variety of languages, dictated by the kernel (default is Python, but more can be added)

Some key jupyter notebook shortcuts:

  • Use shift + enter to run an active cell

  • Use esc in highlighted cell to toggle command options:

    • esc + L = show line numbers

    • esc + M = format cell as Markdown cell

    • esc + a = insert cell above current cell

    • esc + b = insert cell below current cell

  • Check all current variables: run %whos