readme: ---
  license: mit
  ---
  
  
  import nltk
  
  nltk.download('vader_lexicon')
  nltk.download('punkt')
  
  from nltk.sentiment.vader import SentimentIntensityAnalyzer
  
  
  y_pred = []
  sid = SentimentIntensityAnalyzer()
  for row in df_test.iterrows():
      
      sscore = sid.polarity_scores(row[1]['message'])
      if sscore['neg'] >= sscore['pos']:
          y_pred.append(0)
      else:
          y_pred.append(1)