title: ValueError: With n_samples=0, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters
body: <p>I wrote a text classification program. When I run the program it crashes with an error as seen in this screenshot:</p>
  <p><a href="https://i.stack.imgur.com/wDoXv.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/wDoXv.jpg" alt="as seen in this screenshot" /></a></p>
  <blockquote>
  <p>ValueError: With n_samples=0, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters.</p>
  </blockquote>
  <p>Here is my code:</p>
  <pre><code>from sklearn.model_selection import train_test_split
  from gensim.models.word2vec import Word2Vec
  from sklearn.preprocessing import scale
  from sklearn.linear_model import SGDClassifier
  import nltk, string, json
  import numpy as np
  
  def cleanText(corpus):
      reviews = []
      for dd in corpus:
          #for d in dd:
          try:
              words = nltk.word_tokenize(dd['description'])
              words = [w.lower() for w in words]
              reviews.append(words)
              #break
          except:
              pass
      return reviews
  
  with open('C:\\NLP\\bad.json') as fin:
      text = json.load(fin)
      neg_rev = cleanText(text)
  
  with open('C:\\NLP\\good.json') as fin:
      text = json.load(fin)
      pos_rev = cleanText(text)
  
  #1 for positive sentiment, 0 for negative
  y = np.concatenate((np.ones(len(pos_rev)), np.zeros(len(neg_rev))))
  
  x_train, x_test, y_train, y_test = train_test_split(np.concatenate((pos_rev, neg_rev)), y, test_size=0.2)
  </code></pre>
  <p>The data I am using is available here:</p>
  <ol>
  <li><p><a href="https://github.com/SilverYar/TransportDataMiner/blob/master/bad.json" rel="nofollow noreferrer">Bad</a>;</p>
  </li>
  <li><p><a href="https://github.com/SilverYar/TransportDataMiner/blob/master/good.json" rel="nofollow noreferrer">Good</a></p>
  </li>
  </ol>
  <p>How would I go about fixing this error?</p>