texthero.representation.term_frequency¶

term_frequency(s: pandas.core.series.Series, max_features: Union[int, NoneType] = None, return_feature_names=False)¶

Represent a text-based Pandas Series using term_frequency.

Parameters

sPandas Series

max_featuresint, optional

Maximum number of features to keep.

return_features_namesBoolean, False by Default

If True, return a tuple (term_frequency_series, features_names)

Examples

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

To return the features_names:

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