title: deprecation error in sklearn about empty array without any empty array in my code
body: <p>I am just playing around encoding and decoding but I get this error from sklearn:</p>
  
  <blockquote>
    <p>Warning (from warnings module):
      File "C:\Python36\lib\site-packages\sklearn\preprocessing\label.py", line 151
        if diff:
    DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use <code>array.size &gt; 0</code> to check that an array is not empty.</p>
  </blockquote>
  
  <p>Here is the full code, you can run it yourself in python 3+</p>
  
  <p>My question is why is it saying I use an empty array as I clearly don't in my code, thanks for taking your time to answer my question.</p>
  
  <pre><code>### label encoding ###
  
  import numpy as np
  from sklearn import preprocessing
  
  # Sample input labels
  input_labels = ["red", "black", "red", "green",\
                  "black", "yellow", "white"]
  
  # Create label encoder abd fit the label
  encoder = preprocessing.LabelEncoder()
  encoder.fit(input_labels)
  
  # Print the mapping
  print("\nLabel mapping:")
  for i, item in enumerate(encoder.classes_):
      print(item, "--&gt;", i)
  
  # Encode a set of labels using encoder
  test_labels = ["green", "red", "black"]
  encoded_values = encoder.transform(test_labels)
  print("\nLabels =", test_labels)
  print("Encoded values =", list(encoded_values))
  
  # Decode a set of values using the encoder
  encoded_values = [3, 0, 4, 1]
  decoded_list = encoder.inverse_transform(encoded_values)
  print("\nEncoded values =", encoded_values)
  print("Decoded labels=", list(decoded_list))
  </code></pre>