Metadata-Version: 2.1
Name: pdpipe
Version: 0.0.49
Summary: Easy pipelines for pandas.
Home-page: https://pdpipe.github.io/pdpipe/
Author: Shay Palachy
Author-email: shaypal5@gmail.com
License: MIT
Description: pdpipe ˨ 
        ########
        
        |PyPI-Status| |Downloads| |PyPI-Versions| |Build-Status| |Codecov| |Codefactor| |LICENCE|
        
        
        Easy pipelines for pandas DataFrames (`learn how! <https://tirthajyoti.github.io/Notebooks/Pandas-pipeline-with-pdpipe>`_).
        
        Website: `https://pdpipe.github.io/pdpipe/ <https://pdpipe.github.io/pdpipe/>`_
        
        Documentation: `https://pdpipe.github.io/pdpipe/doc/pdpipe/ <https://pdpipe.github.io/pdpipe/doc/pdpipe/>`_
        
        .. code-block:: python
        
          >>> df = pd.DataFrame(
                  data=[[4, 165, 'USA'], [2, 180, 'UK'], [2, 170, 'Greece']],
                  index=['Dana', 'Jane', 'Nick'],
                  columns=['Medals', 'Height', 'Born']
              )
          >>> import pdpipe as pdp
          >>> pipeline = pdp.ColDrop('Medals').OneHotEncode('Born')
          >>> pipeline(df)
                      Height  Born_UK  Born_USA
              Dana     165        0         1
              Jane     180        1         0
              Nick     170        0         0
        
        .. .. alternative symbols: ˨ ᛪ ᛢ ᚶ ᚺ ↬ ⑀ ⤃ ⤳ ⥤ 』
        
        .. contents::
        
        .. section-numbering::
        
        Documentation
        =============
        
        This is the repository of the ``pdpipe`` package, and this readme file is aimed to help potential contributors to the project.
        
        To learn more about how to use ``pdpipe``, either `visit pdpipe's homepage <https://pdpipe.github.io/pdpipe/>`_ or read the `online documentation of pdpipe <https://pdpipe.github.io/pdpipe/doc/pdpipe/>`_.
        
        
        Installation
        ============
        
        Install ``pdpipe`` with:
        
        .. code-block:: bash
        
          pip install pdpipe
        
        Some pipeline stages require ``scikit-learn``; they will simply not be loaded if ``scikit-learn`` is not found on the system, and ``pdpipe`` will issue a warning. To use them you must also `install scikit-learn <http://scikit-learn.org/stable/install.html>`_.
        
        
        Similarly, some pipeline stages require ``nltk``; they will simply not be loaded if ``nltk`` is not found on your system, and ``pdpipe`` will issue a warning. To use them you must additionally `install nltk <http://www.nltk.org/install.html>`_.
        
        
        
        Contributing
        ============
        
        Package author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed, especially since this package is very much in its infancy and many other pipeline stages can be added.
        
        Installing for development
        --------------------------
        
        Clone:
        
        .. code-block:: bash
        
          git clone git@github.com:pdpipe/pdpipe.git
        
        
        Install in development mode with test dependencies:
        
        .. code-block:: bash
        
          cd pdpipe
          pip install -e ".[test]"
        
        
        Running the tests
        -----------------
        
        To run the tests, use:
        
        .. code-block:: bash
        
          python -m pytest
        
        
        Notice ``pytest`` runs are configured by the ``pytest.ini`` file. Read it to understand the exact ``pytest`` arguments used.
        
        
        Adding tests
        ------------
        
        At the time of writing, ``pdpipe`` is maintained with a test coverage of 100%. Although challenging, I hope to maintain this status. If you add code to the package, please make sure you thoroughly test it. Codecov automatically reports changes in coverage on each PR, and so PR reducing test coverage will not be examined before that is fixed.
        
        Tests reside under the ``tests`` directory in the root of the repository. Each model has a separate test folder, with each class - usually a pipeline stage - having a dedicated file (always starting with the string "test") containing several tests (each a global function starting with the string "test"). Please adhere to this structure, and try to separate tests cases to different test functions; this allows us to quickly focus on problem areas and use cases. Thank you! :)
        
        Code style
        ----------
        
        ``pdpip`` code is written to adhere to the coding style dictated by `flake8 <http://flake8.pycqa.org/en/latest/>`_. Practically, this means that one of the jobs that runs on `the project's Travis <https://travis-ci.org/pdpipe/pdpipe>`_ for each commit and pull request checks for a successfull run of the ``flake8`` CLI command in the repository's root. Which means pull requests will be flagged red by the Travis bot if non-flake8-compliant code was added.
        
        To solve this, please run ``flake8`` on your code (whether through your text editor/IDE or using the command line) and fix all resulting errors. Thank you! :)
        
        
        Adding documentation
        --------------------
        
        This project is documented using the `numpy docstring conventions`_, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings (in my personal opinion, of course). When documenting code you add to this project, please follow `these conventions`_.
        
        .. _`numpy docstring conventions`: https://numpydoc.readthedocs.io/en/latest/format.html#docstring-standard
        .. _`these conventions`: https://numpydoc.readthedocs.io/en/latest/format.html#docstring-standard
        
        Additionally, if you update this ``README.rst`` file,  use ``python setup.py checkdocs`` to validate it compiles.
        
        
        Adding doctests
        ---------------
        
        Please notice that for ``pdoc3`` - the Python package used to generate the html documentation files for ``pdpipe`` - to successfully include doctests in the generated documentation files, the whole doctest must be indented in relation to the opening multi-string indentation, like so:
        
        .. code-block:: python
        
        
            class ApplyByCols(PdPipelineStage):
                """A pipeline stage applying an element-wise function to columns.
        
                Parameters
                ----------
                columns : str or list-like
                    Names of columns on which to apply the given function.
                func : function
                    The function to be applied to each element of the given columns.
                result_columns : str or list-like, default None
                    The names of the new columns resulting from the mapping operation. Must
                    be of the same length as columns. If None, behavior depends on the
                    drop parameter: If drop is True, the name of the source column is used;
                    otherwise, the name of the source column is used with the suffix
                    '_app'.
                drop : bool, default True
                    If set to True, source columns are dropped after being mapped.
                func_desc : str, default None
                    A function description of the given function; e.g. 'normalizing revenue
                    by company size'. A default description is used if None is given.
        
        
                Example
                -------
                    >>> import pandas as pd; import pdpipe as pdp; import math;
                    >>> data = [[3.2, "acd"], [7.2, "alk"], [12.1, "alk"]]
                    >>> df = pd.DataFrame(data, [1,2,3], ["ph","lbl"])
                    >>> round_ph = pdp.ApplyByCols("ph", math.ceil)
                    >>> round_ph(df)
                       ph  lbl
                    1   4  acd
                    2   8  alk
                    3  13  alk
                """
        
        
        Credits
        =======
        Created by Shay Palachy  (shay.palachy@gmail.com).
        
        .. alternative:
        .. https://badge.fury.io/py/yellowbrick.svg
        
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Keywords: pandas dataframe pipeline data
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Description-Content-Type: text/x-rst
Provides-Extra: test
Provides-Extra: sklearn
Provides-Extra: nltk
