original_docstring: Extracts salient terms from glass descriptions
      Args:
          glass_descr (str): df with descriptions (raw and tokenised) and sectors
          tokenised_variable (str): name of the variable with tokenised descrs
          sector (str): variable with sector
          word_thres (int): Minimum number of variables to consider
      
docstring: Extracts salient terms from glass descriptions
docstring_tokens: Extracts salient terms from glass descriptions
code: def extract_salient_terms(
      glass_descr, tokenised_variable="tokenised_bi", sector="division", word_thres=75
  ):
      """Extracts salient terms from glass descriptions
      Args:
          glass_descr (str): df with descriptions (raw and tokenised) and sectors
          tokenised_variable (str): name of the variable with tokenised descrs
          sector (str): variable with sector
          word_thres (int): Minimum number of variables to consider
      """
      corpus_freqs = flatten_freq(glass_descr[tokenised_variable])
  
      # Creates a dict
      sector_salient_words = {
          w: get_category_salience(
              glass_descr, sector, w, tokenised_variable, corpus_freqs, thres=75
          )
          for w in sorted(set(glass_w_descr[sector]))
      }
  
      return sector_salient_words
code_tokens: def extract_salient_terms ( glass_descr , tokenised_variable = "tokenised_bi" , sector = "division" , word_thres = 75 ) : corpus_freqs = flatten_freq ( glass_descr [ tokenised_variable ] ) sector_salient_words = { w : get_category_salience ( glass_descr , sector , w , tokenised_variable , corpus_freqs , thres = 75 ) for w in sorted ( set ( glass_w_descr [ sector ] ) ) } return sector_salient_words
short_docstring: Extracts salient terms from glass descriptions
short_docstring_tokens: Extracts salient terms from glass descriptions
comment: """Extracts salient terms from glass descriptions
      Args:
          glass_descr (str): df with descriptions (raw and tokenised) and sectors
          tokenised_variable (str): name of the variable with tokenised descrs
          sector (str): variable with sector
          word_thres (int): Minimum number of variables to consider
      """$SEP$# Creates a dict