{"id":42500557,"url":"https://github.com/jobar8/subsurface_hackathon_2017","last_synced_at":"2026-01-28T13:05:15.633Z","repository":{"id":209538131,"uuid":"94815507","full_name":"jobar8/subsurface_hackathon_2017","owner":"jobar8","description":"Three notebooks to jump start a data science project","archived":false,"fork":false,"pushed_at":"2017-06-21T06:46:54.000Z","size":6356,"stargazers_count":7,"open_issues_count":0,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-01-27T03:41:27.117Z","etag":null,"topics":["data-science","geophysics","groundwater","ipywidgets"],"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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jobar8.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2017-06-19T19:55:41.000Z","updated_at":"2023-11-13T04:34:25.000Z","dependencies_parsed_at":"2023-11-27T23:02:57.293Z","dependency_job_id":null,"html_url":"https://github.com/jobar8/subsurface_hackathon_2017","commit_stats":null,"previous_names":["jobar8/subsurface_hackathon_2017"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jobar8/subsurface_hackathon_2017","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jobar8%2Fsubsurface_hackathon_2017","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jobar8%2Fsubsurface_hackathon_2017/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jobar8%2Fsubsurface_hackathon_2017/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jobar8%2Fsubsurface_hackathon_2017/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jobar8","download_url":"https://codeload.github.com/jobar8/subsurface_hackathon_2017/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jobar8%2Fsubsurface_hackathon_2017/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28845793,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-28T13:02:32.985Z","status":"ssl_error","status_checked_at":"2026-01-28T13:02:04.945Z","response_time":57,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["data-science","geophysics","groundwater","ipywidgets"],"created_at":"2026-01-28T13:05:15.555Z","updated_at":"2026-01-28T13:05:15.625Z","avatar_url":"https://github.com/jobar8.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# subsurface_hackathon_2017\n*Three notebooks to jump start a data science project*\n\nThis repository is associated with a post on my [blog](http://geophysicslabs.com/2017/06/19/three-notebooks-to-jump-start-a-data-science-project/).\n\n---\nThe three Jupyter notebooks that you will find here were originally written during the [Subsurface Hackathon](https://agilescientific.com/blog/2017/6/13/le-grand-hack) that took place in Paris in June 2017. [Martin Bentley](https://github.com/mtb-za) and I were in a team that tried to exploit the free availability of groundwater data from the [Geological Survey of the Netherlands](https://www.dinoloket.nl/en).\n\nThe notebooks provide some examples written in Python for tackling this project, but I think the code is pretty generic and can be used for a large range of other data science projects, especially in geology or geophysics. \n\n![mean_depth_vs_time](./mean_depth_vs_time.png)\n\nWhile much more is certainly possible to achieve with this dataset, I hope this work can help anyone who wants to start a data science project using open data, Python, the pandas library, and Jupyter notebooks.\n\n## Requirements\n\n- Python 3.5\n- pandas 0.20\n- matplotlib 2.0\n- numpy 1.12\n- Scipy 0.19\n- ipywidgets 6.0\n\nNote that the notebooks might certainly work with slightly different configurations - nothing here is cutting edge.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjobar8%2Fsubsurface_hackathon_2017","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjobar8%2Fsubsurface_hackathon_2017","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjobar8%2Fsubsurface_hackathon_2017/lists"}