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-*- mode: rst -*-\n\n|Tests|_ |Codecov|_ |PythonVersion|_ |PyPi|_ |Docs|_\n\n.. |Tests| image:: https://github.com/rodrigo-arenas/scikit-pipes/actions/workflows/ci-tests.yml/badge.svg?branch=master\n.. _Tests: https://github.com/rodrigo-arenas/scikit-pipes/actions/workflows/ci-tests.yml\n\n.. |Codecov| image:: https://codecov.io/gh/rodrigo-arenas/scikit-pipes/branch/master/graphs/badge.svg?branch=master\u0026service=github\n.. _Codecov: https://codecov.io/github/rodrigo-arenas/scikit-pipes?branch=master\n\n.. |PythonVersion| image:: https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9-blue\n.. _PythonVersion : https://www.python.org/downloads/\n\n.. |PyPi| image:: https://badge.fury.io/py/scikit-pipes.svg\n.. _PyPi: https://badge.fury.io/py/scikit-pipes\n\n.. |Docs| image:: https://readthedocs.org/projects/scikit-pipes/badge/?version=latest\n.. _Docs: https://scikit-pipes.readthedocs.io/en/latest/?badge=latest\n\n.. |Contributors| image:: https://contributors-img.web.app/image?repo=rodrigo-arenas/scikit-pipes\n.. _Contributors: https://github.com/rodrigo-arenas/scikit-pipes/graphs/contributors\n\n\n.. image:: https://github.com/rodrigo-arenas/scikit-pipes/blob/master/docs/images/logo16.png?raw=true\n   :width: 100\n\nScikit-Pipes\n############\n\nScikit-Learn practical pre-defined Pipelines Hub.\n\nThis package is still at an experimental stage.\n\nUsage:\n######\n\nInstall scikit-pipes\n\nWe advise to install scikit-pipes using a virtual env, inside the env use::\n\n   pip install scikit-pipes\n\nExample: Simple Preprocessing\n#############################\n\n.. code-block:: python\n\n    import pandas as pd\n    import numpy as np\n    from skpipes.pipeline import SkPipeline\n\n    data = [{\"x1\": 1, \"x2\": 400, \"x3\": np.nan},\n            {\"x1\": 4.8, \"x2\": 250, \"x3\": 50},\n            {\"x1\": 3, \"x2\": 140, \"x3\": 43},\n            {\"x1\": 1.4, \"x2\": 357, \"x3\": 75},\n            {\"x1\": 2.4, \"x2\": np.nan, \"x3\": 42},\n            {\"x1\": 4, \"x2\": 287, \"x3\": 21}]\n\n    df = pd.DataFrame(data)\n\n    pipe = SkPipeline(name='median_imputer-minmax',\n                      data_type=\"numerical\")\n    pipe.steps\n    str(pipe)\n\n    pipe.fit(df)\n    pipe.transform(df)\n    pipe.fit_transform(df)\n\n\nChangelog\n#########\n\nSee the `changelog \u003chttps://scikit-pipes.readthedocs.io/en/latest/release_notes.html\u003e`__\nfor notes on the changes of Sklearn-pipes\n\nImportant links\n###############\n\n- Official source code repo: https://github.com/rodrigo-arenas/scikit-pipes/\n- Download releases: https://pypi.org/project/scikit-pipes/\n- Issue tracker: https://github.com/rodrigo-arenas/scikit-pipes/issues\n- Stable documentation: https://scikit-pipes.readthedocs.io/en/stable/\n\nSource code\n###########\n\nYou can check the latest development version with the command::\n\n   git clone https://github.com/rodrigo-arenas/scikit-pipes.git\n\nInstall the development dependencies::\n\n  pip install -r dev-requirements.txt\n\nCheck the latest in-development documentation: https://scikit-pipes.readthedocs.io/en/latest/\n\nContributing\n############\n\nContributions are always welcome!\nIf you want to contribute, make sure to read the `Contribution guide \u003chttps://github.com/rodrigo-arenas/scikit-pipes/blob/master/CONTRIBUTING.md\u003e`_.\n\nThanks to the people who are helping with this project!\n\n|Contributors|_\n\nTesting\n#######\n\nAfter installation, you can launch the test suite from outside the source directory::\n\n   pytest skpipes\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frodrigo-arenas%2Fscikit-pipes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frodrigo-arenas%2Fscikit-pipes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frodrigo-arenas%2Fscikit-pipes/lists"}