old_contents: from collections import defaultdict
  from nltk.corpus import stopwords
  import pandas as pd
  import re
  
  def clean():
      # download nltk sets if you haven't already
      #nltk.download()
  
      # file to pull candidate, county, votes & tweets from
      candidate_data = pd.read_csv('NH_Data.csv')
      tweet_list = []
      
      candidate_data['Tweet list'] = candidate_data['Tweet list'].fillna('')
      
      x = 0
      word_list = []
      all_words_list = []
      stop_words = set(stopwords.words("english"))
      stop_words.add('n')
      
      while x < len(candidate_data['Tweet list']):
          words = re.sub('[^\w-]', ' ', candidate_data['Tweet list'][x])
          word_list = words.split()
          word_list = [w for w in word_list if not w in stop_words]
          a_big_string = ', '.join(word_list)
          candidate_data['Tweet list'][x] = a_big_string
          x = x + 1
      
      return candidate_data
  
  #result = clean()
new_contents: from collections import defaultdict
  from nltk.corpus import stopwords
  import pandas as pd
  import re
  
  def clean():
      # download nltk sets if you haven't already
      #nltk.download()
  
      # file to pull candidate, county, votes & tweets from
      candidate_data = pd.read_csv('NH_Data.csv')
      tweet_list = []
      
      candidate_data['Tweet List'] = candidate_data['Tweet List'].fillna('')
      
      x = 0
      word_list = []
      all_words_list = []
      stop_words = set(stopwords.words("english"))
      stop_words.add('n')
      
      while x < len(candidate_data['Tweet List']):
          words = re.sub('[^\w-]', ' ', candidate_data['Tweet List'][x])
          word_list = words.split()
          word_list = [w for w in word_list if not w in stop_words]
          a_big_string = ', '.join(word_list)
          candidate_data['Tweet List'][x] = a_big_string
          x = x + 1
      
      return candidate_data
  
  #result = clean()
  
subject: Update cleaning.py