Created
September 18, 2012 21:00
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Inspecting scikit-learn CountVectorizer output with a Pandas DataFrame
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>>> from pandas import DataFrame | |
>>> from sklearn.feature_extraction.text import CountVectorizer | |
>>> docs = ["You can catch more flies with honey than you can with vinegar.", | |
... "You can lead a horse to water, but you can't make him drink."] | |
>>> vect = CountVectorizer(min_df=0., max_df=1.0) | |
>>> X = vect.fit_transform(docs) | |
>>> print(DataFrame(X.A, columns=vect.get_feature_names()).to_string()) | |
but can catch drink flies him honey horse lead make more than to vinegar water with you | |
0 0 2 1 0 1 0 1 0 0 0 1 1 0 1 0 2 2 | |
1 1 2 0 1 0 1 0 1 1 1 0 0 1 0 1 0 2 |
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