Wrapper library for text cleansing, preprocessing in NLP
Project description
Maleo
Wrapper library for text cleansing, preprocessing in NLP
Overview of features
- Scanner : get insight about your text dataset (ex: number of chars, words, emojis, etc)
- Remove hyperlink, punctuation, stopword, emoticon, etc
- Extract hashtags, price from text
- Convert email, phone number, date to <TAG>
- Convert Indonesian slang to formal word
- Convert emoji to word or <TAG>
- Convert word to number
- Predict Part-of-Speech (POS) tags
Installation
pip install maleo
Getting Started
from maleo.wizard import Wizard
wiz = Wizard()
wiz.scanner(df, 'text')
wiz.emoji_to_word(df.text)
wiz.slang_to_formal(df.text)
wiz.load_pos()
wiz.predict_pos('saya mau pergi beli makan siang dulu', output_pair=False)
Instance Attribute
['scanner',
'rm_multiple_space',
'rm_link',
'rm_punc',
'rm_char',
'rm_html',
'rm_non_ascii',
'rm_stopword',
'rm_emoticon',
'word_to_number',
'get_hashtag',
'get_price',
'email_to_tag',
'date_to_tag',
'phone_num_to_tag',
'slang_to_formal',
'emoji_to_word',
'emoji_to_tag',
'custom_regex',
'predict_pos']
Universal POS tags
https://universaldependencies.org/u/pos/index.html
Contributor:
- Ruben Stefanus
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