def remove_brackets(s: TextSeries) -> TextSeries:
"""
Remove content within brackets and the brackets itself.
Remove content from any kind of brackets, (), [], {}, <>.
Examples
--------
>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series("Texthero (round) [square] [curly] [angle]")
>>> hero.remove_brackets(s)
0 Texthero
dtype: object
See also
--------
:meth:`remove_round_brackets`
:meth:`remove_curly_brackets`
:meth:`remove_square_brackets`
:meth:`remove_angle_brackets`
"""
return (s.pipe(remove_round_brackets).pipe(remove_curly_brackets).pipe(
remove_square_brackets).pipe(remove_angle_brackets))
def has_content(s: TextSeries) -> TextSeries:
r"""
Return a Boolean Pandas Series indicating if the rows have content.
Examples
--------
>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series(["content", np.nan, "\t\n", " "])
>>> hero.has_content(s)
0 True
1 False
2 False
3 False
dtype: bool
"""
return (s.pipe(remove_whitespace) != "") & (~s.isna())
def clean(s: TextSeries, pipeline=None) -> TextSeries:
"""
Pre-process a text-based Pandas Series, by using the following default
pipeline.
Default pipeline:
1. :meth:`texthero.preprocessing.fillna`
2. :meth:`texthero.preprocessing.lowercase`
3. :meth:`texthero.preprocessing.remove_digits`
4. :meth:`texthero.preprocessing.remove_html_tags`
5. :meth:`texthero.preprocessing.remove_punctuation`
6. :meth:`texthero.preprocessing.remove_diacritics`
7. :meth:`texthero.preprocessing.remove_stopwords`
8. :meth:`texthero.preprocessing.remove_whitespace`
Parameters
----------
s : :class:`texthero._types.TextSeries`
pipeline : List[Callable[Pandas Series, Pandas Series]],
optional, default=None
Specific pipeline to clean the texts. Has to be a list
of functions taking as input and returning as output
a Pandas Series. If None, the default pipeline
is used.
Examples
--------
For the default pipeline:
>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series("Uper 9dig. he her ÄÖÜ")
>>> hero.clean(s)
0 uper 9dig aou
dtype: object
"""
if not pipeline:
pipeline = get_default_pipeline()
for f in pipeline:
s = s.pipe(f)
return s
def restore_tweets(
s: TextSeries, pipeline=get_twitter_post_pipeline()) -> TextSeries:
"""
Pre-process a text-based Pandas Series of tweets, by using the following
pipeline.
Twitter pipeline:
1. :meth:`texthero.preprocessing.fillna`
2. :meth:`texthero.preprocessing.replace_emojis`
3. :meth:`texthero.preprocessing.replace_urls`
Parameters
----------
s : :class:`texthero._types.TextSeries`
pipeline : List[Callable[Pandas Series, Pandas Series]],
optional, default=None
Specific pipeline to clean the texts. Has to be a list
of functions taking as input and returning as output
a Pandas Series. If None, the default pipeline
is used.
Examples
--------
For the default pipeline:
>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series("the book of the jungle 😈 https://example.com")
>>> hero.clean_tweets(s)
0 the book of the jungle :smiling_face_with_horns: <URL>
dtype: object
"""
if not pipeline:
pipeline = get_twitter_post_pipeline()
for f in pipeline:
s = s.pipe(f)
return s
def clean(s: TextSeries, pipeline=None) -> TextSeries:
"""
Pre-process a text-based Pandas Series, by using the following default
pipeline.
Default pipeline:
1. :meth:`texthero.preprocessing.fillna`
2. :meth:`texthero.preprocessing.lowercase`
3. :meth:`texthero.preprocessing.remove_digits`
4. :meth:`texthero.preprocessing.remove_punctuation`
5. :meth:`texthero.preprocessing.remove_diacritics`
6. :meth:`texthero.preprocessing.remove_stopwords`
7. :meth:`texthero.preprocessing.remove_whitespace`
Parameters
----------
s : :class:`texthero._types.TextSeries`
pipeline :List[Callable[[Pandas Series], Pandas Series]]
inserting specific pipeline to clean a text
Examples
--------
For the default pipeline:
>>> import texthero as hero
>>> import pandas as pd
>>> s = pd.Series("Uper 9dig. he her ÄÖÜ")
>>> hero.clean(s)
0 uper 9dig aou
dtype: object
"""
if not pipeline:
pipeline = get_default_pipeline()
for f in pipeline:
s = s.pipe(f)
return s
