Metadata-Version: 2.1
Name: scikit-datasets
Version: 0.2.1
Summary: Scikit-learn-compatible datasets
Author-email: David Diaz Vico <david.diaz.vico@outlook.com>, Carlos Ramos Carreño <vnmabus@gmail.com>
Maintainer-email: David Diaz Vico <david.diaz.vico@outlook.com>, Carlos Ramos Carreño <vnmabus@gmail.com>
License: MIT License
        
        Copyright (c) 2017 David Díaz Vico
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: homepage, https://github.com/daviddiazvico/scikit-datasets
Project-URL: documentation, https://daviddiazvico.github.io/scikit-datasets/
Project-URL: repository, https://github.com/daviddiazvico/scikit-datasets
Project-URL: download, https://github.com/daviddiazvico/scikit-datasets/archive/v0.2.1.tar.gz
Keywords: scikit-learn,datasets,repository,benchmark,Python
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: cran
Provides-Extra: forex
Provides-Extra: keel
Provides-Extra: keras
Provides-Extra: physionet
Provides-Extra: utils-estimator
Provides-Extra: utils-experiments
Provides-Extra: utils-scores
Provides-Extra: all
Provides-Extra: test
License-File: LICENSE

# scikit-datasets
Scikit-learn-compatible datasets

## Status
[![Tests](https://github.com/daviddiazvico/scikit-datasets/actions/workflows/tests.yml/badge.svg)](https://github.com/daviddiazvico/scikit-datasets/actions/workflows/tests.yml)
[![Maintainability](https://api.codeclimate.com/v1/badges/a37c9ee152b41a0cb577/maintainability)](https://codeclimate.com/github/daviddiazvico/scikit-datasets/maintainability)
[![Test Coverage](https://api.codeclimate.com/v1/badges/a37c9ee152b41a0cb577/test_coverage)](https://codeclimate.com/github/daviddiazvico/scikit-datasets/test_coverage)
[![Build Status](https://dev.azure.com/daviddiazvico0337/daviddiazvico/_apis/build/status/daviddiazvico.scikit-datasets?branchName=master)](https://dev.azure.com/daviddiazvico0337/daviddiazvico/_build/latest?definitionId=1&branchName=master)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6383047.svg)](https://doi.org/10.5281/zenodo.6383047)

## Installation
Available in [PyPI](https://pypi.python.org/pypi?:action=display&name=scikit-datasets)
```
pip install scikit-datasets
```

## Documentation
Autogenerated and hosted in [GitHub Pages](https://daviddiazvico.github.io/scikit-datasets/)

## Distribution
Run the following command from the project home to create the distribution
```
python setup.py sdist bdist_wheel
```
and upload the package to [testPyPI](https://testpypi.python.org/)
```
twine upload --repository-url https://test.pypi.org/legacy/ dist/*
```
or [PyPI](https://pypi.python.org/)
```
twine upload dist/*
```

## Citation
If you find scikit-datasets useful, please cite it in your publications.
You can find the appropriate citation format in the sidebar, in both APA and
Bibtex.
