{ "info": { "author": "Ulf Hamster", "author_email": "554c46@gmail.com", "bugtrack_url": null, "classifiers": [], "description": "[![Build Status](https://travis-ci.org/kmedian/onehot.svg?branch=master)](https://travis-ci.org/kmedian/onehot)\n[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/kmedian/onehot/master?urlpath=lab)\n\n# onehot.OneHotDummy\nOne-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly.\n\n[onehot.OneHotDummy](onehot/onehotdummy_class.py) does basically the same as [LabelEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html) and [OneHotEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html) combined. It is also inspired by [pandas.get_dummies](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html) and in particular its ease of use. \n\n\n\n## Table of Contents\n* [Installation](#installation)\n* [Usage](#usage)\n* [Commands](#commands)\n* [Support](#support)\n* [Contributing](#contributing)\n\n\n## Installation\nThe `onehot` [git repo](http://github.com/kmedian/onehot) is available as [PyPi package](https://pypi.org/project/onehot)\n\n```\npip install onehot\n```\n\n\n## Usage\nCheck the [examples](examples) folder for notebooks.\n\n\n## Commands\n* Check syntax: `flake8 --ignore=F401`\n\n* Remove `.pyc` files: `find . -type f -name \"*.pyc\" | xargs rm`\n* Remove `__pycache__` folders: `find . -type d -name \"__pycache__\" | xargs rm -rf`\n* Upload to PyPi: `python setup.py sdist upload -r pypi`\n* Upload to PyPi with twine: `python setup.py sdist && twine upload -r pypi dist/*`\n\n\n## Debugging\n* Notebooks to profile python code are in the [profile](profile) folder\n\n\n## Support\nPlease [open an issue](https://github.com/kmedian/onehot/issues/new) for support.\n\n\n## Contributing\nPlease contribute using [Github Flow](https://guides.github.com/introduction/flow/). 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