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Merge pull request #40 from sinhrks/v2.0
REL: v2.0.0
2 parents fb4bed1 + cc56110 commit 708d68d

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README.rst

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pandas-ml
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=========
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.. image:: https://pypip.in/version/expandas/badge.svg
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:target: https://pypi.python.org/pypi/expandas/
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.. image:: https://pypip.in/version/pandas_ml/badge.svg
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:target: https://pypi.python.org/pypi/pandas_ml/
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:alt: Latest Version
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.. image:: https://readthedocs.org/projects/pandas-ml/badge/?version=latest
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Expand pandas functionalities to be easier to use other statistics/ML packages, mainly forcusing on scikit-learn.
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Installation
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~~~~~~~~~~~~
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.. code-block::
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$ pip install pandas_ml
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Documentation
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~~~~~~~~~~~~~
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pandas_ml/skaccessors/test/test_semi_supervised.py

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import sklearn.datasets as datasets
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import sklearn.semi_supervised as ss
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import pandas_ml as expd
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import pandas_ml as pdml
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import pandas_ml.util.testing as tm
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class TestSemiSupervised(tm.TestCase):
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def test_objectmapper(self):
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df = expd.ModelFrame([])
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df = pdml.ModelFrame([])
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self.assertIs(df.semi_supervised.LabelPropagation, ss.LabelPropagation)
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self.assertIs(df.semi_supervised.LabelSpreading, ss.LabelSpreading)
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def test_Classifications(self):
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iris = datasets.load_iris()
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df = expd.ModelFrame(iris)
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df = pdml.ModelFrame(iris)
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models = ['LabelPropagation', 'LabelSpreading']
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for model in models:
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result = df.predict(mod1)
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expected = mod2.predict(iris.data)
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self.assertTrue(isinstance(result, expd.ModelSeries))
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self.assertTrue(isinstance(result, pdml.ModelSeries))
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self.assert_numpy_array_almost_equal(result.values, expected)
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pandas_ml/version.py

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version = '0.2.0dev'
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version = '0.2.0'

setup.py

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README = 'README.rst'
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REQUIREMENTS = 'requirements.txt'
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VERSION = '0.2.0dev'
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VERSION = '0.2.0'
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def read(fname):
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# file must be read as utf-8 in py3 to avoid to be bytes

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