A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

Xarray Tutorial

An open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun.
https://github.com/xarray-contrib/xarray-tutorial

Category: Sustainable Development
Sub Category: Education

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hacktoberfest

Keywords from Contributors

pangeo zarr pydata data-catalog climate compressed geoscience climate-model transform finite-volume

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Xarray Tutorials

README.md

Xarray Tutorial

CI
Jupyter Book Badge
Binder

This is the repository for a Jupyter Book website with tutorial material for 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 - "a development environment that's hosted in the cloud"

Open in GitHub Codespaces

☝️ 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, 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 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 Interface.

Locally

You can also run these notebooks on your own computer! We recommend using pixi to ensure a fully reproducible Python environment:

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 document.

Thanks to our contributors so far!

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. Funding for SciPy 2022, SciPy 2023 tutorial material development specifically was supported by NASA's Open Source Tools, Frameworks, and Libraries Program (award 80NSSC22K0345).


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Last synced: 6 days ago

Total Commits: 218
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Avg Commits per committer: 6.056
Development Distribution Score (DDS): 0.784

Commits in past year: 36
Committers in past year: 14
Avg Commits per committer in past year: 2.571
Development Distribution Score (DDS) in past year: 0.667

Name Email Commits
Deepak Cherian d****n 47
Scott Henderson s****h@u****u 30
Joseph Hamman j****n@u****u 29
dependabot[bot] 4****] 22
pre-commit-ci[bot] 6****] 18
Anderson Banihirwe a****e@u****u 9
keewis k****s 9
Jessica Scheick J****1 8
Negin Sobhani n****s@u****u 6
Don Setiawan l****s@u****u 6
Ryan Abernathey r****y@g****m 3
Emma Marshall 5****l 3
Max Jones 1****s 2
Tom Nicholas t****s@c****u 2
Zachary Moon z****2@g****m 2
qheuristics g****r@g****m 2
Guen Prawiroatmodjo g****p@m****m 1
Bijal B. Patel b****d@o****m 1
Yuta Norden 6****n 1
Willi Rath w****h 1
Wietze w****e@s****m 1
Wei Ji 2****4 1
Tyler Erickson t****n@g****m 1
Tien Vo t****k@p****e 1
Shunichiro Nomura s****5@g****m 1
RichardScottOZ 7****Z 1
Pavithra Eswaramoorthy p****s@o****m 1
Michal W. Tarnowski m****i@h****m 1
Matthew Plough m****h@k****m 1
Luis López b****n@g****m 1
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Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 46
Total pull requests: 97
Average time to close issues: 6 months
Average time to close pull requests: 13 days
Total issue authors: 10
Total pull request authors: 23
Average comments per issue: 2.22
Average comments per pull request: 2.15
Merged pull request: 88
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Bot pull requests: 35

Past year issues: 9
Past year pull requests: 10
Past year average time to close issues: 3 months
Past year average time to close pull requests: 2 months
Past year issue authors: 3
Past year pull request authors: 6
Past year average comments per issue: 0.22
Past year average comments per pull request: 2.2
Past year merged pull request: 8
Past year bot issues: 0
Past year bot pull requests: 5

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Top Issue Authors

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Dependencies

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pyproject.toml pypi
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conda/environment.yml pypi

Score: 8.92585319042092