https://github.com/xarray-contrib/xarray-tutorial
Xarray Tutorials
https://github.com/xarray-contrib/xarray-tutorial
hacktoberfest
Last synced: about 1 month ago
JSON representation
Xarray Tutorials
- Host: GitHub
- URL: https://github.com/xarray-contrib/xarray-tutorial
- Owner: xarray-contrib
- License: apache-2.0
- Created: 2018-08-28T21:40:12.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2025-04-07T19:09:31.000Z (3 months ago)
- Last Synced: 2025-04-30T14:15:55.509Z (about 2 months ago)
- Topics: hacktoberfest
- Language: Jupyter Notebook
- Homepage: https://tutorial.xarray.dev/
- Size: 102 MB
- Stars: 186
- Watchers: 11
- Forks: 113
- Open Issues: 24
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# Xarray Tutorial
[](https://github.com/xarray-contrib/xarray-tutorial/actions?query=branch%3Amain)
[](https://tutorial.xarray.dev)
[](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD?labpath=workshops/scipy2024/index.ipynb)
This is the repository for a Jupyter Book website with tutorial material for [Xarray](https://github.com/pydata/xarray), _an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun!_
The website is hosted at https://tutorial.xarray.dev
Tutorials are written as interactive Jupyter Notebooks with executable code examples that you can easily run and modify:
#### On the Cloud
All notebooks can be run via the Mybinder.org 'Launch Binder' badge at the top of this page. This will load a pre-configured JupyterLab interface with all tutorial notebooks for you to run. _You have minimal computing resources and any changes you make will not be saved._
#### Github Codespaces
This tutorial is available to run within [Github Codespaces](https://github.com/features/codespaces) - "a development environment that's hosted in the cloud"
[](https://codespaces.new/xarray-contrib/xarray-tutorial/tree/main)
☝️ Click the button above to go to options window to launch a Github codespace.
GitHub currently gives every user [120 vCPU hours per month for free](https://docs.github.com/en/billing/managing-billing-for-github-codespaces/about-billing-for-github-codespaces#monthly-included-storage-and-core-hours-for-personal-accounts), beyond that you must pay. **So be sure to explicitly stop or shut down your codespace when you are done by going to this page (https://github.com/codespaces).**
Once your codespace is launched, the following happens:
- [Visual Studio Code](https://code.visualstudio.com/) Interface will open up within your browser.
- A built in terminal will open and it will execute `jupyter lab` automatically.
- Once you see a url to click within the terminal, simply `cmd + click` the given url.
- This will open up another tab in your browser, leading to a [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/) Interface.
#### Locally
You can also run these notebooks on your own computer! We recommend using [`pixi`](https://pixi.sh/latest/#installation) to ensure a fully reproducible Python environment:
```bash
git clone https://github.com/xarray-contrib/xarray-tutorial.git
cd xarray-tutorial
pixi run tutorial
```
## Contributing
Contributions are welcome and greatly appreciated! See our [CONTRIBUTING.md](./CONTRIBUTING.md) document.
Thanks to our contributors so far!
[](https://github.com/xarray-contrib/xarray-tutorial/graphs/contributors)
## Acknowledgements
This website is the result of many contributions from the Xarray community! We're very grateful for everyone's volunteered effort as well as [sponsored development](https://xarray.dev/#sponsors). Funding for SciPy 2022, SciPy 2023 tutorial material development specifically was supported by NASA's Open Source Tools, Frameworks, and Libraries Program (award 80NSSC22K0345).