Metadata-Version: 2.0
Name: pdtransform
Version: 0.2
Summary: Sklearn transformers that work with Pandas dataframes
Home-page: http://signal-to-noise.xyz/why-you-should-use-scikit-learns-pipeline-object.html
Author: Michele Lacchia
Author-email: michelelacchia@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Keywords: sklearn pandas transformers pipeline
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Requires-Dist: scikit-learn
Requires-Dist: pandas

sklearn-pdtransform
-------------------

Installation:

.. code::

    $ pip install pdtransform

A little package with a few transformers to work with Pandas dataframes in the
Sklearn pipeline, which I found myself writing quite frequently. Example usage:

.. code:: python

   from pdtransform import DFTransform, DFFeatureUnion

   pipeline = Pipeline([
       ('ordinal_to_nums', DFTransform(_ordinal_to_nums, copy=True)),
       ('union', DFFeatureUnion([
           ('categorical', Pipeline([
               ('select', DFTransform(lambda X: X.select_dtypes(include=['object']))),
               ('fill_na', DFTransform(lambda X: X.fillna('NA'))),
               ('one_hot', DFTransform(_one_hot_encode)),
           ])),
           ('numerical', Pipeline([
               ('select', DFTransform(lambda X: X.select_dtypes(exclude=['object']))),
               ('fill_median', DFTransform(lambda X: X.fillna(X.median()))),
               ('add_features', DFTransform(_add_features, copy=True)),
               ('remove_skew', DFTransform(_remove_skew, copy=True)),
               ('find_outliers', DFTransform(_find_outliers, copy=True)),
               ('normalize', DFTransform(lambda X: X.div(X.max())))
           ])),
       ])),
   ])


For more information read `this blog post <http://signal-to-noise.xyz/why-you-should-use-scikit-learns-pipeline-object.html>`_.


