{"id":21564999,"url":"https://github.com/mahtabranjbar/geospatial-clustering","last_synced_at":"2026-02-02T22:45:20.634Z","repository":{"id":195072034,"uuid":"674737571","full_name":"MahtabRanjbar/Geospatial-Clustering","owner":"MahtabRanjbar","description":"This project performs geospatial clustering on a dataset of latitude and longitude coordinates to identify clusters of points.","archived":false,"fork":false,"pushed_at":"2023-09-15T09:36:38.000Z","size":3544,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-18T05:17:18.113Z","etag":null,"topics":["clustering","machine-learning","unsupervised-learning"],"latest_commit_sha":null,"homepage":"","language":"HTML","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/MahtabRanjbar.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":"2023-08-04T16:35:45.000Z","updated_at":"2023-09-15T18:12:18.000Z","dependencies_parsed_at":null,"dependency_job_id":"5d0eea45-e3c2-4132-921e-82656248fa2c","html_url":"https://github.com/MahtabRanjbar/Geospatial-Clustering","commit_stats":{"total_commits":9,"total_committers":1,"mean_commits":9.0,"dds":0.0,"last_synced_commit":"68016c8e49ac03ed335d672ae50f9ca8cd1520ae"},"previous_names":["mahtabranjbar/geospatial-clustering"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MahtabRanjbar/Geospatial-Clustering","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahtabRanjbar%2FGeospatial-Clustering","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahtabRanjbar%2FGeospatial-Clustering/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahtabRanjbar%2FGeospatial-Clustering/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahtabRanjbar%2FGeospatial-Clustering/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MahtabRanjbar","download_url":"https://codeload.github.com/MahtabRanjbar/Geospatial-Clustering/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahtabRanjbar%2FGeospatial-Clustering/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263437327,"owners_count":23466363,"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":["clustering","machine-learning","unsupervised-learning"],"created_at":"2024-11-24T10:18:00.451Z","updated_at":"2026-02-02T22:45:15.607Z","avatar_url":"https://github.com/MahtabRanjbar.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Geospatial Clustering\n\nThis project performs geospatial clustering on a dataset of latitude and longitude coordinates to identify clusters of points.\n\n## Clustering Report\nI have performed clustering analysis on the dataset and the results can be found in **reports** folder.\nyou can also see Clustering report [here](reports/README.md)\n\n\n## Installation\n\nTo use this project, you will need to have Python 3 and `conda` installed on your computer. You can download Python 3 from the [official website](https://www.python.org/downloads/) and `conda` from the [official website](https://docs.conda.io/en/latest/miniconda.html).\n\nOnce you have installed Python 3 and `conda`, you can create an environment for this project by running the following command in the root directory of the project:\n\n```sh\nconda create --name geo_cluster python=3.9\n```\n\nThis will create a new conda environment named geo_cluster with Python 3.9 installed. You can activate this environment by running the following command:\n\n```sh\nconda activate geo_cluster\n```\nOnce you have activated the cancer_clf environment, you can install the necessary libraries for this project by running the following command in the root directory of the project:\n\n```sh\npip install -r requirements.txt\n```\nThis will install the libraries listed in the requirements.txt file using conda. Once you have installed these libraries, you can use this project as described in the Usage section.\n\n\n## Usage\n\nTo use this project, you will need to set the `PYTHONPATH` environment variable to the root directory of the project. You can do this by running the following command in the root directory of the project:\n\n```sh\nexport PYTHONPATH=${PWD}\n```\n\nOnce you have set the `PYTHONPATH` environment variable, you can run the main script of the project by running the following command in the `src` directory of the project:\n\n```sh\npython src/main.py\n```\n\nThis will load and preprocess the data, train the clustering models, evaluate their performance, visualize the clusters, and generate a report.\n\nThe report will be saved as a Markdown file in the `reports` directory. You can view the report using a Markdown viewer or convert it to another format such as HTML or PDF using a Markdown converter.\n\n\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahtabranjbar%2Fgeospatial-clustering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmahtabranjbar%2Fgeospatial-clustering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahtabranjbar%2Fgeospatial-clustering/lists"}