{"id":18483938,"url":"https://github.com/computingvictor/insurance-company-benchmark-practice","last_synced_at":"2026-05-16T11:06:16.376Z","repository":{"id":62754019,"uuid":"559917019","full_name":"ComputingVictor/Insurance-Company-Benchmark-Practice","owner":"ComputingVictor","description":"1st Practice for the subject of Machine Learning","archived":false,"fork":false,"pushed_at":"2022-12-30T22:33:53.000Z","size":1327,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-16T08:06:29.001Z","etag":null,"topics":["cunef","data-science","eda","insurance-company","jupyter-notebook","machine-learning","python"],"latest_commit_sha":null,"homepage":"","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/ComputingVictor.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}},"created_at":"2022-10-31T11:22:29.000Z","updated_at":"2022-12-31T09:40:56.000Z","dependencies_parsed_at":"2023-01-31T17:02:08.747Z","dependency_job_id":null,"html_url":"https://github.com/ComputingVictor/Insurance-Company-Benchmark-Practice","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ComputingVictor/Insurance-Company-Benchmark-Practice","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ComputingVictor%2FInsurance-Company-Benchmark-Practice","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ComputingVictor%2FInsurance-Company-Benchmark-Practice/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ComputingVictor%2FInsurance-Company-Benchmark-Practice/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ComputingVictor%2FInsurance-Company-Benchmark-Practice/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ComputingVictor","download_url":"https://codeload.github.com/ComputingVictor/Insurance-Company-Benchmark-Practice/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ComputingVictor%2FInsurance-Company-Benchmark-Practice/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33100321,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-16T04:41:52.686Z","status":"ssl_error","status_checked_at":"2026-05-16T04:41:52.009Z","response_time":115,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 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":["cunef","data-science","eda","insurance-company","jupyter-notebook","machine-learning","python"],"created_at":"2024-11-06T12:37:57.152Z","updated_at":"2026-05-16T11:06:16.329Z","avatar_url":"https://github.com/ComputingVictor.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Insurance Company Benchmark (COIL 2000) Practice\n\n\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https://hips.hearstapps.com/hmg-prod.s3.amazonaws.com/images/gettyimages-1321202626.jpg?resize=480:*\" /\u003e\u003c/div\u003e.\n\n## About the project\n\nThe \"Insurance Company Benchmark\" database contains a series of records from different clients. Each client record contains sociodemographic attributes and values ​​that indicate the number of policies contracted on different goods. \n\nThe business objective is, through the point of view of an insurer, to predict, using the data we have, whether a client will sign a mobile home insurance policy or not.\n\n\n**For this practice, at the moment, we will have to perform only an exploratory data analysis of the dataset**.\n\nFind the dataset [here](https://archive-beta.ics.uci.edu/ml/datasets/insurance+company+benchmark+coil+2000#Descriptive)\n\n\n\n## Built with \n\n\n- Python 3.9.12\n- Jupyter Notebook\n\n## Content of the repository\n\n- `data`: \n    - `Raw`: Documents downloaded from the source of the dataset.\n    - `Processed data`: Data dictionay processed.\n\n- `docs`: Complementary files of the notebook with functions ( Py files).\n\n- `notebooks`: Notebooks of the project\n\n\n## Roadmap\n\n- [x] EDA\n- [ ] Data Modelation\n- [ ] Data Validation\n- [ ] Deployment \u0026 Optimization\n\n\n\n## Contact\n\nVíctor Viloria Vázquez - \u003cvictor.viloria@cunef.edu\u003e\n\nProject Link: \u003chttps://github.com/ComputingVictor/Insurance-Company-Benchmark-Practice\u003e\n\nLinkedin - \u003chttps://www.linkedin.com/in/vicviloria/\u003e\n\n\n\n\u003ca href=\"#top\"\u003eBack to top\u003c/a\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcomputingvictor%2Finsurance-company-benchmark-practice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcomputingvictor%2Finsurance-company-benchmark-practice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcomputingvictor%2Finsurance-company-benchmark-practice/lists"}