{"id":18646918,"url":"https://github.com/jonad/finding_donors","last_synced_at":"2026-05-03T17:33:58.488Z","repository":{"id":129494156,"uuid":"80166960","full_name":"jonad/finding_donors","owner":"jonad","description":"Predicting income with UCI Census Income Dataset using supervised machine learning algorithms","archived":false,"fork":false,"pushed_at":"2017-11-28T22:45:14.000Z","size":775,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-17T19:07:46.759Z","etag":null,"topics":["numpy","pandas","scikit-learn","scikitlearn-machine-learning"],"latest_commit_sha":null,"homepage":"","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/jonad.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-01-26T23:48:22.000Z","updated_at":"2017-11-29T01:08:31.000Z","dependencies_parsed_at":"2023-06-11T11:15:30.842Z","dependency_job_id":null,"html_url":"https://github.com/jonad/finding_donors","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jonad/finding_donors","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonad%2Ffinding_donors","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonad%2Ffinding_donors/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonad%2Ffinding_donors/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonad%2Ffinding_donors/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jonad","download_url":"https://codeload.github.com/jonad/finding_donors/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonad%2Ffinding_donors/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32578723,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T06:36:36.687Z","status":"ssl_error","status_checked_at":"2026-05-03T06:36:09.306Z","response_time":103,"last_error":"SSL_read: 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":["numpy","pandas","scikit-learn","scikitlearn-machine-learning"],"created_at":"2024-11-07T06:23:29.549Z","updated_at":"2026-05-03T17:33:58.472Z","avatar_url":"https://github.com/jonad.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Supervised Learning\n## Project: Finding Donors for CharityML\n\n### Install\n\nThis project requires **Python 2.7** and the following Python libraries installed:\n\n- [NumPy](http://www.numpy.org/)\n- [Pandas](http://pandas.pydata.org)\n- [matplotlib](http://matplotlib.org/)\n- [scikit-learn](http://scikit-learn.org/stable/)\n\nYou will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)\n\nWe recommend students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. \n\n### Run\n\nIn a terminal or command window, navigate to the top-level project directory `finding_donors/` (that contains this README) and run one of the following commands:\n\n```bash\nipython notebook finding_donors.ipynb\n```  \nor\n```bash\njupyter notebook finding_donors.ipynb\n```\n### Data\n\nThe modified census dataset consists of approximately 32,000 data points, with each datapoint having 13 features. This dataset is a modified version of the dataset published in the paper *\"Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid\",* by Ron Kohavi. You may find this paper [online](https://www.aaai.org/Papers/KDD/1996/KDD96-033.pdf), with the original dataset hosted on [UCI](https://archive.ics.uci.edu/ml/datasets/Census+Income).\n\n**Features**\n- `age`: Age\n- `workclass`: Working Class (Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked)\n- `education_level`: Level of Education (Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool)\n- `education-num`: Number of educational years completed\n- `marital-status`: Marital status (Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse)\n- `occupation`: Work Occupation (Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces)\n- `relationship`: Relationship Status (Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried)\n- `race`: Race (White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black)\n- `sex`: Sex (Female, Male)\n- `capital-gain`: Monetary Capital Gains\n- `capital-loss`: Monetary Capital Losses\n- `hours-per-week`: Average Hours Per Week Worked\n- `native-country`: Native Country (United-States, Cambodia, England, Puerto-Rico, Canada, Germany, Outlying-US(Guam-USVI-etc), India, Japan, Greece, South, China, Cuba, Iran, Honduras, Philippines, Italy, Poland, Jamaica, Vietnam, Mexico, Portugal, Ireland, France, Dominican-Republic, Laos, Ecuador, Taiwan, Haiti, Columbia, Hungary, Guatemala, Nicaragua, Scotland, Thailand, Yugoslavia, El-Salvador, Trinadad\u0026Tobago, Peru, Hong, Holand-Netherlands)\n\n**Target Variable**\n- `income`: Income Class (\u003c=50K, \u003e50K)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonad%2Ffinding_donors","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonad%2Ffinding_donors","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonad%2Ffinding_donors/lists"}