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The Jupyter Notebook is an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text.
The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R.
For this workshop, we will be using R via Jupyter
Notebooks are a great tool for exploration and for documenting your workflow. Notebooks allow you to write:
- Code
- Plots
- Formatted text
- Latex text for equations
and much more in a single document!
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R is the programming language that runs computations.
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Jupyter is an integrated development environment (IDE) that provides an interface by adding convenient features and tools.
You can think of Jupyter Notebooks as the dashboard of a car.
You don’t drive a car by interacting with the engine but rather by interacting with the car’s dashboard.
In the same way, rather than interacting with R directly, we will be using the Jupyter's interface.
Jupyter will allow us to:
- Run R code interactively
- Use other languages such as Python, Julia, or Matlab!
This is what a Jupyter Notebook looks like:
- Notebooks are great for exploration and for documenting your workflow
- There are many options for sharing notebooks in human readable format:
- Share online with nbviewer.jupyter.org
- Github renders automatically any notebooks that you push.
- You can convert to HTML, PDF, etc. with nbconvert