{"id":23922605,"url":"https://github.com/datenhahn/munich-bicycle-prediction","last_synced_at":"2026-06-21T14:31:24.458Z","repository":{"id":180227551,"uuid":"656034657","full_name":"datenhahn/munich-bicycle-prediction","owner":"datenhahn","description":"This project uses opendata of the city of Munich to predict the expected number of cyclists for a given day using the weather forecast and historic data.","archived":false,"fork":false,"pushed_at":"2023-07-19T16:42:49.000Z","size":6223,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-23T22:28:16.692Z","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/datenhahn.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-06-20T06:16:53.000Z","updated_at":"2023-10-06T17:00:30.000Z","dependencies_parsed_at":"2024-01-04T16:44:05.171Z","dependency_job_id":null,"html_url":"https://github.com/datenhahn/munich-bicycle-prediction","commit_stats":null,"previous_names":["ecodia/munich-bicycle-prediction","datenhahn/munich-bicycle-prediction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/datenhahn/munich-bicycle-prediction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datenhahn%2Fmunich-bicycle-prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datenhahn%2Fmunich-bicycle-prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datenhahn%2Fmunich-bicycle-prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datenhahn%2Fmunich-bicycle-prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/datenhahn","download_url":"https://codeload.github.com/datenhahn/munich-bicycle-prediction/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datenhahn%2Fmunich-bicycle-prediction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34613041,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-21T02:00:05.568Z","response_time":54,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2025-01-05T17:15:10.678Z","updated_at":"2026-06-21T14:31:24.440Z","avatar_url":"https://github.com/datenhahn.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Science Project - Predicting cyclists in Munich\n\nThis project uses opendata of the city of Munich to predict the expected number of cyclists for a given day using the weather forecast and historic data.\n\nBlogpost:\n\nhttps://medium.com/@jonas.hahn/open-data-predicting-cyclist-traffic-in-munich-4acf1c11c0ed\n\n## Getting Started\n\nTo run the webapp via docker execute the following commands:\n\n```\ndocker-compose up\n```\n\nThe webapp is then available at http://localhost:8080\n\n![](blogpost/screenshot-webapp.png)\n\n## Project Structure\n\nThe project is structured as follows:\n\n* `blogpost` : Contains the blogpost as markdown file and the images used in the blogpost on medium.com\n* `datasources` : Contains the scripts to download and clean the data.\n* `explorations` : Contains the jupyter notebooks used for data exploration and model experimentation.\n* `models` : Contains the finalized version of the model training pipeline and the trained model.\n* `webapp` : Contains the webapp to predict the number of cyclists for a given day.\n\n## Train the model\n\nTo train the model, execute the following command:\n\n```\npython3 train_model.py --inputdata ../datasources/munich-bicycle-counting-stations/cleaned/bicycle-counting-station-daily.json\n```\n\n## Datasources\n\nEvery datasource has its own folder in the `datasources` folder, which contains detailed documentation and scripts or jupyter notebooks to download and clean the data.\n\n* **Munich Bicycle Counting Stations** : \"Bicycle counting stations\" were established in Munich in 2008 for continuous monitoring of increasing bicycle traffic. This is the main dataset used, you find details in the datasets README\n\n### Munich Bicycle Counting Stations\n\nSee the readme file `datasources/munich-bicycle-counting-stations/README.md`\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatenhahn%2Fmunich-bicycle-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatenhahn%2Fmunich-bicycle-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatenhahn%2Fmunich-bicycle-prediction/lists"}