{"id":13465398,"url":"https://github.com/feature-engine/feature-engine-examples","last_synced_at":"2025-04-23T09:03:29.953Z","repository":{"id":42661225,"uuid":"393355979","full_name":"feature-engine/feature-engine-examples","owner":"feature-engine","description":null,"archived":false,"fork":false,"pushed_at":"2025-01-29T17:11:58.000Z","size":2752,"stargazers_count":34,"open_issues_count":1,"forks_count":19,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-04-23T09:03:06.578Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://feature-engine.readthedocs.io/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/feature-engine.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE.md","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,"zenodo":null},"funding":{"github":["solegalli"],"buy_me_a_coffee":"solegalliy"}},"created_at":"2021-08-06T11:26:26.000Z","updated_at":"2025-04-08T10:31:34.000Z","dependencies_parsed_at":"2024-07-31T15:01:14.628Z","dependency_job_id":"8b591d17-8a52-4971-8b44-9e133bc87225","html_url":"https://github.com/feature-engine/feature-engine-examples","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feature-engine%2Ffeature-engine-examples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feature-engine%2Ffeature-engine-examples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feature-engine%2Ffeature-engine-examples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feature-engine%2Ffeature-engine-examples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/feature-engine","download_url":"https://codeload.github.com/feature-engine/feature-engine-examples/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250403834,"owners_count":21424794,"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":[],"created_at":"2024-07-31T15:00:29.003Z","updated_at":"2025-04-23T09:03:29.934Z","avatar_url":"https://github.com/feature-engine.png","language":"Jupyter Notebook","readme":"# Jupyter notebooks with Demos of Feature-engine's functionality\n\n![PythonVersion](https://img.shields.io/badge/python-3.6%20|3.7%20|%203.8%20|%203.9-success)\n[![License https://github.com/feature-engine/feature_engine/blob/master/LICENSE.md](https://img.shields.io/badge/license-BSD-success.svg)](https://github.com/feature-engine/feature-engine-examples/blob/master/LICENSE.md)\n[![Sponsorship https://www.trainindata.com/](https://img.shields.io/badge/Powered%20By-TrainInData-orange.svg)](https://www.trainindata.com/)\n\n\nFeature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. \nFeature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the \ntransforming parameters from data and then transform the data.\n\nIn this repo, you will find a lot of examples on how to use Feature-engine's transformers on various datasets. The notebooks are sorted in the following folders and include examples for the following transformers:\n\n\n## creation\n * MathFeatures\n * RelativeFeatures\n * CyclicalFeatures\n\n## discretisation\n* EqualFrequencyDiscretiser\n* EqualFrequencyDiscretiser plus WoEEncoder\n* EqualWidthDiscretiser\n* EqualWidthDiscretiser plus OrdinalEncoder\n* DecisionTreeDiscretiser\n* ArbitraryDiscreriser\n* ArbitraryDiscreriser plus MeanEncoder\n\n## encoding\n* OneHotEncoder\n* OrdinalEncoder\n* CountFrequencyEncoder\n* MeanEncoder\n* WoEEncoder\n* PRatioEncoder\n* RareLabelEncoder\n* DecisionTreeEncoder\n\n## imputation\n* MeanMedianImputer\n* RandomSampleImputer\n* EndTailImputer\n* AddMissingIndicator\n* CategoricalImputer\n* ArbitraryNumberImputer\n* DropMissingData -- notebook wanted, please contribute\n\n## outliers\n* Winsorizer\n* ArbitraryOutlierCapper\n* OutlierTrimmer\n\n## pipelines\n* create new features - wine data\n* regression pipeline - house prices data\n* more notebooks wanted, please constribute\n\n## transformation\n* LogTransformer\n* LogCpTransformer\n* ReciprocalTransformer\n* PowerTransformer\n* BoxCoxTransformer\n* YeoJohnsonTransformer\n\n### wrappers\n * SklearnTransformerWrapper plus Scikit-learn's OneHotEncoder\n * SklearnTransformerWrapper plus Scikit-learn's feature selection classes\n * SklearnTransformerWrapper plus Scikit-learn's KBinsDiscretizer\n * SklearnTransformerWrapper plus Scikit-learn's Scalers\n * SklearnTransformerWrapper plus Scikit-learn's SimpleImputer\n\n## selection\n * notebooks wanted, please contribute\n\n\n\n# Contributing\n\nWe welcome notebooks from users of the package. If you want to create one of the missing notebooks, or want to add a notebook of your own, provided that the data set is free to share, make a pull request with the code.\n\nHow to contribute:\n\n### Local Setup Steps\n- Fork the repo\n- Clone your fork into your local computer: ``git clone https://github.com/\u003cYOURUSERNAME\u003e/feature-engine-examples.git``\n- cd into the repo ``cd feature-engine-examples``\n- If you haven't done so yet, install feature-engine ``pip install feature_engine``\n- Create a feature branch with a meaningful name for your notebook: ``git checkout -b mynotebookbranch``\n- Develop your notebook\n- Add the changes to your copy of the fork: ``git add .``, ``git commit -m \"a meaningful commit message\"``, ``git pull origin mynotebookbranch:mynotebookbranch``\n- Go to your fork on Github and make a PR to this repo\n- Done\n\nThank you!!\n\n## Feature-engine features in the following resources\n\n* [Feature Engineering for Machine Learning, Online Course](https://www.trainindata.com/p/feature-engineering-for-machine-learning)\n\n* [Feature Selection for Machine Learning, Online Course](https://www.trainindata.com/p/feature-selection-for-machine-learning)\n\n* [Feature Engineering for Time Series Forecasting, Online Course](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n\n* [Forecasting with Machine Learning, Online Course](https://www.trainindata.com/p/forecasting-with-machine-learning)\n\n* [Python Feature Engineering Cookbook](https://www.packtpub.com/en-us/product/python-feature-engineering-cookbook-9781835883587)\n\n* [Feature Selection in Machine Learning Book](https://www.trainindata.com/p/feature-selection-in-machine-learning-book)\n\n\n## Blogs about Feature-engine\n\n* [Feature-engine: A new open-source Python package for feature engineering](https://trainindata.medium.com/feature-engine-a-new-open-source-python-package-for-feature-engineering-29a0ab88ea7c)\n\n* [Practical Code Implementations of Feature Engineering for Machine Learning with Python](https://towardsdatascience.com/practical-code-implementations-of-feature-engineering-for-machine-learning-with-python-f13b953d4bcd)\n\n\n## Documentation\n\n* [Documentation](https://feature-engine.trainindata.com)\n\n## En Español:\n\n* [Ingeniería de variables, MachinLenin, charla online](https://www.youtube.com/watch?v=NhCxOOoFXds)\n","funding_links":["https://github.com/sponsors/solegalli","https://buymeacoffee.com/solegalliy"],"categories":["Jupyter Notebook"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeature-engine%2Ffeature-engine-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffeature-engine%2Ffeature-engine-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeature-engine%2Ffeature-engine-examples/lists"}