{"id":14977793,"url":"https://github.com/numpy/numpy-tutorials","last_synced_at":"2025-05-15T05:07:39.024Z","repository":{"id":39999351,"uuid":"248354526","full_name":"numpy/numpy-tutorials","owner":"numpy","description":"NumPy tutorials \u0026 educational content in notebook format","archived":false,"fork":false,"pushed_at":"2025-05-01T14:19:48.000Z","size":189084,"stargazers_count":553,"open_issues_count":20,"forks_count":196,"subscribers_count":34,"default_branch":"main","last_synced_at":"2025-05-12T06:23:17.831Z","etag":null,"topics":["numpy","tutorials"],"latest_commit_sha":null,"homepage":"https://numpy.org/numpy-tutorials/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/numpy.png","metadata":{"funding":{"open_collective":"numpy","tidelift":"pypi/numpy","custom":"https://numpy.org/about/#donate"},"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-03-18T22:13:22.000Z","updated_at":"2025-05-10T03:38:56.000Z","dependencies_parsed_at":"2023-12-21T21:25:09.307Z","dependency_job_id":"b18b8024-d1d4-4c35-95b1-ff6b1d72f04d","html_url":"https://github.com/numpy/numpy-tutorials","commit_stats":{"total_commits":296,"total_committers":28,"mean_commits":"10.571428571428571","dds":0.6114864864864865,"last_synced_commit":"552fcd08a574ede9fa1ce1e131d71edf73ebd523"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/numpy%2Fnumpy-tutorials","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/numpy%2Fnumpy-tutorials/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/numpy%2Fnumpy-tutorials/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/numpy%2Fnumpy-tutorials/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/numpy","download_url":"https://codeload.github.com/numpy/numpy-tutorials/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254276447,"owners_count":22043867,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["numpy","tutorials"],"created_at":"2024-09-24T13:56:20.764Z","updated_at":"2025-05-15T05:07:38.989Z","avatar_url":"https://github.com/numpy.png","language":"Python","readme":"# NumPy tutorials\n\n_For the rendered tutorials, see https://numpy.org/numpy-tutorials/._\n\nThe goal of this repository is to provide high-quality resources by the\nNumPy project, both for self-learning and for teaching classes with. If you're\ninterested in adding your own content, check the [Contributing](#contributing)\nsection. This set of tutorials and educational materials is not a part of the\nNumPy source tree.\n\nTo download a local copy of the `.ipynb` files, you can either\n[clone this repository](https://docs.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository)\nor navigate to any of the documents listed below and download it individually.\n\n## Content\n\n0. [Learn to write a NumPy tutorial](content/tutorial-style-guide.md): our style guide for writing tutorials.\n1. [Tutorial: Linear algebra on n-dimensional arrays](content/tutorial-svd.md)\n2. [Tutorial: Determining Moore's Law with real data in NumPy](content/mooreslaw-tutorial.md)\n3. [Tutorial: Saving and sharing your NumPy arrays](content/save-load-arrays.md)\n4. [Tutorial: NumPy deep learning on MNIST from scratch](content/tutorial-deep-learning-on-mnist.md)\n5. [Tutorial: X-ray image processing](content/tutorial-x-ray-image-processing.md)\n6. [Tutorial: NumPy deep reinforcement learning with Pong from pixels](content/tutorial-deep-reinforcement-learning-with-pong-from-pixels.md)\n7. [Tutorial: Masked Arrays](content/tutorial-ma.md)\n8. [Tutorial: Static Equilibrium](content/tutorial-static_equilibrium.md)\n9. [Tutorial: Plotting Fractals](content/tutorial-plotting-fractals.ipynb)\n10. [Tutorial: NumPy natural language processing from scratch with a focus on ethics](content/tutorial-nlp-from-scratch.md)\n11. [Tutorial: Analysing the impact of the lockdown on air quality in Delhi, India](content/tutorial-air-quality-analysis.md)\n\n\n## Contributing\n\nWe very much welcome contributions! If you have an idea or proposal for a new\ntutorial, please [open an issue](https://github.com/numpy/numpy-tutorials/issues)\nwith an outline.\n\nDon’t worry if English is not your first language, or if you can only come up\nwith a rough draft. Open source is a community effort. Do your best – we’ll help\nfix issues.\n\nImages and real-life data make text more engaging and powerful, but be sure what\nyou use is appropriately licensed and available. Here again, even a rough idea\nfor artwork can be polished by others.\n\nThe NumPy tutorials are a curated collection of\n[MyST-NB](https://myst-nb.readthedocs.io/) notebooks. These notebooks are used\nto produce static websites and can be opened as notebooks in Jupyter using\n[Jupytext](https://jupytext.readthedocs.io).\n\n\u003e __Note:__ You should use [CommonMark](https://commonmark.org) markdown\n\u003e cells. Jupyter only renders CommonMark.\n\n### Why Jupyter Notebooks?\n\nThe choice of Jupyter Notebook in this repo instead of the usual format\n([reStructuredText, through Sphinx](https://www.sphinx-doc.org/en/master/usage/restructuredtext/index.html))\nused in the main NumPy documentation has two reasons:\n\n * Jupyter notebooks are a common format for communicating scientific\n   information.\n * Jupyter notebooks can be launched in [Binder](https://www.mybinder.org), so that users can interact\n   with tutorials\n * rST may present a barrier for some people who might otherwise be very\n   interested in contributing tutorial material.\n\n#### Note\n\nYou may notice our content is in markdown format (`.md` files). We review and\nhost notebooks in the [MyST-NB](https://myst-nb.readthedocs.io/) format. We\naccept both Jupyter notebooks (`.ipynb`) and MyST-NB notebooks (`.md`). If you want\nto sync your `.ipynb` to your `.md` file follow the [pairing\ntutorial](content/pairing.md).\n\n### Adding your own tutorials\n\nIf you have your own tutorial in the form of a Jupyter notebook (a `.ipynb`\nfile) and you'd like to add it to the repository, follow the steps below.\n\n\n#### Create an issue\n\nGo to [https://github.com/numpy/numpy-tutorials/issues](https://github.com/numpy/numpy-tutorials/issues)\nand create a new issue with your proposal. Give as much detail as you can about\nwhat kind of content you would like to write (tutorial, how-to) and what you\nplan to cover. We will try to respond as quickly as possible with comments, if\napplicable.\n\n#### Check out our suggested template\n\nYou can use our [Tutorial Style Guide](content/tutorial-style-guide.md) to make\nyour content consistent with our existing tutorials.\n\n#### Upload your content\n\n\u003cul\u003e\n\u003cdetails\u003e\n    \u003csummary\u003e\n        \u003cb\u003eFork this repository\u003c/b\u003e (if you haven't before).\n    \u003c/summary\u003e\n    \u003cimg src=\"site/_static/01-fork.gif\" width=80% height=80%\u003e\n\u003c/details\u003e\n\n\u003cdetails\u003e\n    \u003csummary\u003e\n        \u003cb\u003eIn your own fork, create a new branch for your content.\u003c/b\u003e\n    \u003c/summary\u003e\n    \u003cimg src=\"site/_static/02-create_new_branch.gif\" width=80% height=80%\u003e\n\u003c/details\u003e\n\n\u003cdetails\u003e\n    \u003csummary\u003e\n        \u003cb\u003eAdd your notebook to the \u003ccode\u003econtent/\u003c/code\u003e directory.\u003c/b\u003e\n    \u003c/summary\u003e\n    \u003cimg src=\"site/_static/03-upload.gif\" width=80% height=80%\u003e\n\u003c/details\u003e\n\n\u003cb\u003eUpdate the \u003ccode\u003eenvironment.yml\u003c/code\u003e file with the dependencies for your\ntutorial\u003c/b\u003e (only if you add new dependencies).\n\n\u003cdetails\u003e\n    \u003csummary\u003e\n        \u003cb\u003eUpdate this \u003ccode\u003eREADME.md\u003c/code\u003e to include your new entry.\u003c/b\u003e\n    \u003c/summary\u003e\n    \u003cimg src=\"site/_static/04-add_to_readme.gif\" width=80% height=80%\u003e\n\u003c/details\u003e\n\n\u003cb\u003eUpdate the attribution section (below) to credit the original tutorial\nauthor, if applicable.\u003c/b\u003e\n\n\u003cdetails\u003e\n    \u003csummary\u003e\n        \u003cb\u003eCreate a \u003ca href=\"https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/about-pull-requests\"\u003epull request.\u003c/a\u003e\n        Make sure the \"Allow edits and access to secrets by maintainers\" option\n        is selected so we can properly review your submission.\u003c/b\u003e\n    \u003c/summary\u003e\n    \u003cimg src=\"site/_static/05-create_PR.gif\" width=80% height=80%\u003e\n\u003c/details\u003e\n\n:tada: \u003cb\u003eWait for review!\u003c/b\u003e\n\u003c/ul\u003e\n\nFor more information about GitHub and its workflow, you can see\n[this document](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests).\n\n\n### Building the Sphinx site locally\n\nBuilding the tutorials website, which is published at\nhttps://github.com/numpy/numpy-tutorials, locally isn't necessary before making\na contribution, but may be helpful:\n\n```bash\nconda env create -f environment.yml\nconda activate numpy-tutorials\ncd site\nmake html\n```\n\n## Translations\n\nWhile we don't have the capacity to translate and maintain translated versions\nof these tutorials, you are free to use and translate them to other languages.\n\n## Useful links and resources\n\nThe following links may be useful:\n\n- [NumPy Code of Conduct](https://numpy.org/doc/stable/dev/conduct/code_of_conduct.html)\n- [Main NumPy documentation](https://numpy.org/doc/stable/)\n- [NumPy documentation team meeting notes](https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg?both)\n- [NEP 44 - Restructuring the NumPy documentation](https://numpy.org/neps/nep-0044-restructuring-numpy-docs.html)\n- [Blog post - Documentation as a way to build Community](https://labs.quansight.org/blog/2020/03/documentation-as-a-way-to-build-community/)\n\nNote that regular documentation issues for NumPy can be found in the [main NumPy\nrepository](https://github.com/numpy/numpy/issues) (see the `Documentation`\nlabels there).\n\n","funding_links":["https://opencollective.com/numpy","https://tidelift.com/funding/github/pypi/numpy","https://numpy.org/about/#donate"],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnumpy%2Fnumpy-tutorials","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnumpy%2Fnumpy-tutorials","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnumpy%2Fnumpy-tutorials/lists"}