docstr: Parameters
  ----------
  term_ranker : TermRanker
      Default AbsoluteFrequencyRanker
  minimum_term_count : int
      Default 0
  usage_portion : float
      Portion of times term is used in a containing n-gram for it to be eliminated
      Default 0.8
  verbose : bool
      Show progress bar
docstr_tok: ["Parameters","--","--","--","--","--","term_ranker",":","TermRanker","Default","AbsoluteFrequencyRanker","minimum_term_count",":","int","Default","0","usage_portion",":","float","Portion","of","times","term","is","used","in","a","containing","n-gram","for","it","to","be","eliminated","Default","0.8","verbose",":","bool","Show","progress","bar"]
code: def __init__(
      self,
      term_ranker: type = AbsoluteFrequencyRanker,
      minimum_term_count: int = 0,
      usage_portion: float = 0.7,
      verbose: bool = False,
  ):
      """
  
      Parameters
      ----------
      term_ranker : TermRanker
          Default AbsoluteFrequencyRanker
      minimum_term_count : int
          Default 0
      usage_portion : float
          Portion of times term is used in a containing n-gram for it to be eliminated
          Default 0.8
      verbose : bool
          Show progress bar
      """
      self.term_ranker = term_ranker
      self.minimum_term_count = minimum_term_count
      self.usage_portion = usage_portion
      self.verbose = verbose
  
file_path: scattertext/scattertext/termcompaction/ngram_percentage_compactor.py
imports: import abc
  import pandas
  from tqdm.auto import tqdm
  from scattertext.TermDocMatrixWithoutCategories import TermDocMatrixWithoutCategories
  from scattertext.features.featoffsets.flexible_ngram_features import sequence_window
  from scattertext.termranking import AbsoluteFrequencyRanker
label_desc: Use image node_id 1 to create a new NgramPercentageCompactor object from inherited base classes: BaseTermCompactor with example: obj = NgramPercentageCompactor(term_ranker, minimum_term_count, usage_portion, verbose)