A simplified method for cleaning text by specifying as True/False what to clean from a text.Clean text by removing emails,numbers,stopwords,emojis,etc.remove_emojis () > print ( result ) 'This is the mail ,our WEBSITE is and it will cost $100 to subscribe.' Clean Text read_txt ( 'file.txt' ) Chaining Methods on TextFrame > t1 = "This is the mail ,our WEBSITE is □ and it will cost $100 to subscribe." > docx = TextFrame ( t1 ) > result = docx. Alternatively you can instantiate a TextFrame and read a text file into it.fix_contractions () Handling Files with NeatText normalize ( level = 'deep' ) 'this is the mail examplegmailcom our website is httpsexamplecom ' > docx. normalize () 'this is the mail ,our website is □.' > docx. readability () Basic NLP Task (Tokenization,Ngram,Text Generation) > docx. length 73 > # Scan Percentage of Noise(Unclean data) in text > d. describe () Key Value Length : 73 vowels : 21 consonants : 34 stopwords : 4 punctuations : 8 special_char : 8 tokens ( whitespace ): 10 tokens ( words ): 14 > docx. text "This is the mail ,our WEBSITE is □." > docx. > import neattext as nt > mytext = "This is the mail ,our WEBSITE is □." > docx = nt.
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