texthero.representation.tfidf¶

tfidf(s: pandas.core.series.Series, max_features=None, min_df=1, return_feature_names=False)¶

Represent a text-based Pandas Series using TF-IDF.

Parameters

sPandas Series

max_featuresint, optional

Maximum number of features to keep.

min_dfint, optional. Default to 1.

When building the vocabulary ignore terms that have a document frequency strictly lower than the given threshold.

return_features_namesBoolean. Default to False.

If True, return a tuple (tfidf_series, features_names)

Examples

>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series(["Sentence one", "Sentence two"])
>>> hero.tfidf(s)
0    [0.5797386715376657, 0.8148024746671689, 0.0]
1    [0.5797386715376657, 0.0, 0.8148024746671689]
dtype: object

To return the feature_names:

>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series(["Sentence one", "Sentence two"])
>>> hero.tfidf(s, return_feature_names=True)
(0    [0.5797386715376657, 0.8148024746671689, 0.0]
1    [0.5797386715376657, 0.0, 0.8148024746671689]
dtype: object, ['Sentence', 'one', 'two'])