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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
@@ -17,6 +17,14 @@ Overview
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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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+
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+ .. code-block ::
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+
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+ $ pip install pandas_ml
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+
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Documentation
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~~~~~~~~~~~~~
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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 :
@@ -33,7 +33,7 @@ def test_Classifications(self):
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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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Original file line number Diff line number Diff line change 1
- version = '0.2.0dev '
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+ version = '0.2.0 '
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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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