title: Scatter plot multiclass labels
body: <p>I'm trying to implement <code>SMOTE</code> technic and thus I would like to visualize my labels. This technic helps me solve the data imbalance problem. </p>
  
  <p>I have, say, 1000 labels of <code>1, 2, and 3</code> and the counts are <code>100, 100, 800</code> respectively. After <code>SMOTE</code>, I will add synthetic values so that I will have <code>800, 800, and 800</code> for <code>1, 2, and 3</code> labels. </p>
  
  <p>Now I want to plot these labels before and after <code>SMOTE</code>. I have divided my dataset into <code>train_X</code> and <code>train_y</code>. I tried to adjust iris code to my dataset but I failed. This is what I tried (does not draw anything and giving <code>ValueError: 'c' argument has 154 elements, which is not acceptable for use with 'x' with size 25, 'y' with size 25.</code> error):</p>
  
  <pre><code>from matplotlib import pyplot as plt
  
  features = train_X
  target = train_y.values.ravel()
  
  plt.scatter(features[0], features[1], alpha=0.2,
              s=100*features[3], c=target, cmap='viridis')
  plt.xlabel("L1")
  plt.ylabel("L2");
  plt.show()
  </code></pre>
  
  <p>How can I plot my labels with different colors so that I can take a look how the values are distributed?</p>