Most of the tutorial content here is written as Jupyter Notebooks that mix code, text, visualization, and exercises. You can either browse rendered versions of these notebooks on this website, or execute the code examples interactively.
You have two options for executing notebooks:
1. On the Cloud: Clicking will load a pre-configured Jupyter Lab interface with all tutorial notebooks for you to run. You have minimal computing resources and any changes you make will not be saved. Any page with executable content also has a icon in the upper right that will launch an interactive session for that particular page.
Be patient, it can take a few minutes for a server to become available on the Cloud (Mybinder.org)!
1. On your computer: Running tutorials on your computer requires some setup:
We recommend using
conda-lock to ensure a fully reproducible Python environment
git clone https://github.com/xarray-contrib/xarray-tutorial.git cd xarray-tutorial conda-lock install conda/conda-lock.yml --name xarray-tutorial # Or latest package versions: `mamba env create -f conda/environment-unpinned.yml` conda activate xarray-tutorial jupyter lab
Tutorials are approximately divided into sections with increasing levels of complexity:
Advanced. You’ll also find content specific to various
Workshops hosted over the years, often with accompanying video recordings of instructors going over content and answering questions that come up.
JupyterLab is a next-generation web-based user interface for Project Jupyter. If you are new to this interface, spend some time reviewing the documentation and videos.
If you haven’t used the Jupyter Notebooks before, the quick intro is
There are two modes: command and edit
From command mode, press Enter to edit a cell (like this markdown cell)
From edit mode, press Esc to change to command mode
Press shift+enter to execute a cell and move to the next cell.
The toolbar has commands for executing, converting, and creating cells.