{"id":16200023,"url":"https://github.com/chilipp/psyplot-data-science-symposium-20240404","last_synced_at":"2025-04-07T17:48:14.986Z","repository":{"id":231517024,"uuid":"781900906","full_name":"Chilipp/psyplot-Data-Science-Symposium-20240404","owner":"Chilipp","description":"Presentation of psyplot on the 9th Data Science Symposium, April 4th 2024","archived":false,"fork":false,"pushed_at":"2024-04-04T11:29:06.000Z","size":52297,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-13T19:51:13.428Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc-by-4.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Chilipp.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-04-04T09:00:19.000Z","updated_at":"2024-04-04T09:57:16.000Z","dependencies_parsed_at":"2024-04-04T12:44:38.534Z","dependency_job_id":null,"html_url":"https://github.com/Chilipp/psyplot-Data-Science-Symposium-20240404","commit_stats":null,"previous_names":["chilipp/psyplot-data-science-symposium-20240404"],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chilipp%2Fpsyplot-Data-Science-Symposium-20240404","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chilipp%2Fpsyplot-Data-Science-Symposium-20240404/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chilipp%2Fpsyplot-Data-Science-Symposium-20240404/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chilipp%2Fpsyplot-Data-Science-Symposium-20240404/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Chilipp","download_url":"https://codeload.github.com/Chilipp/psyplot-Data-Science-Symposium-20240404/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247704408,"owners_count":20982291,"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":[],"created_at":"2024-10-10T09:29:04.663Z","updated_at":"2025-04-07T17:48:14.961Z","avatar_url":"https://github.com/Chilipp.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Using psyplot for visualizing unstructured data and vertical transects\n\nData Science Symposium\n\nApril 4th, 2024\n\nPhilipp S. Sommer\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Chilipp/psyplot-Data-Science-Symposium-20240404/main?filepath=psyplot-framework-presentation.ipynb)\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10925983.svg)](https://doi.org/10.5281/zenodo.10925983)\n\nThis presentation demonstrates the most recent features of Psyplot, a powerful tool for visualizing climate data on unstructured grids. The utilization of UGRID conventions has become paramount in handling unstructured grids effectively. This presentation demonstrates how psyplot can be used to effectively and straightforwardly visualize climate data conforming to UGRID conventions, highlighting its role in enhancing the comprehension of spatial and temporal patterns.\n\nAnother key focus of the presentation is on the grid-independent extraction of vertical transects in 4-dimensional data, addressing a critical challenge in climate science. I will showcase the new innovative methodologies within Psyplot that facilitate seamless extraction of vertical profiles across varying grid structures, enabling researchers to analyze and interpret climate variables. By showcasing practical applications and case studies, the presentation aims to demonstrate the usefullness of psyplot for climate data analysis and model development. Attendees will gain valuable insights into the potential of Psyplot and its role in pushing the boundaries of visualizing climate data on unstructured grids.\n\n\n\n## About this presentation\n\nThis presentation is a new version of the presentation on the \n[KS Institute Seminar in February 2022][KS-Seminar]. Some parts have been \nshown interactively in the GUI during the presentation.\n\n[KS-Seminar]: https://github.com/Chilipp/psyplot-KS-Seminar-20240201\n\n\n## Note\n\nThis presentation is a jupyter notebook presented with [RISE][rise]. You can\naccess the raw notebook at\n[psyplot-framework-presentation.ipynb](psyplot-framework-presentation.ipynb).\n\nYou can also execute the cells in this presentation interactively by clicking\non\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Chilipp/psyplot-Data-Science-Symposium-20240404/main?filepath=psyplot-framework-presentation.ipynb)\n\n\n## License\n\nThe contents of this repository is published under the Creative Commons\nAttribution 4.0 International Public License (CC BY 4.0).\n\nSee the [LICENSE](LICENSE) file for more details.\n\nCopyright (c) 2022-2024, Helmholtz-Zentrum hereon GmbH\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchilipp%2Fpsyplot-data-science-symposium-20240404","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchilipp%2Fpsyplot-data-science-symposium-20240404","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchilipp%2Fpsyplot-data-science-symposium-20240404/lists"}