title: Pyplot cannot plot Regression
body: <p>I am trying to emulate the very simple example</p>
  
  <pre><code>N = 50
  x = np.random.rand(N)
  y = np.random.rand(N)
  colors = np.random.rand(N)
  area = np.pi * (15 * np.random.rand(N))**2  # 0 to 15 point radiuses
  
  print(type(x),type(y))
  print('training samples ',len(x),len(y))
  plt.scatter(x, y, c=colors, alpha=0.5)
  plt.show()
  </code></pre>
  
  <p>this shows</p>
  
  <pre><code>&lt;class 'numpy.ndarray'&gt; &lt;class 'numpy.ndarray'&gt;
  training samples  50 50
  </code></pre>
  
  <p>as expected and the plot shows up as well. Now I am trying to plot the results of <code>GradientBoostingRegressor</code> as </p>
  
  <pre><code>base_regressor = GradientBoostingRegressor()
  base_regressor.fit(X_train, y_train)
  y_pred_base = base_regressor.predict(X_test)
  
  print(type(X_train),type(y_train))
  print('training samples ',len(X_train),len(y_train))
  print(type(X_test),type(y_pred_base))
  print('base samples ',len(X_test),len(y_pred_base))
  
  plt.figure()
  
  plt.scatter(X_train, y_train, c="k", label="training samples")
  plt.plot(X_test, y_pred_base, c="g", label="n_estimators=1", linewidth=2)
  plt.xlabel("data")
  plt.ylabel("target")
  plt.title("Base Regression")
  plt.legend()
  plt.show()
  </code></pre>
  
  <p>note that <code>X_train</code>, <code>y_train</code>, and <code>X_test</code> are all numpy arrays. For the above code I get</p>
  
  <pre><code>&lt;class 'numpy.ndarray'&gt; &lt;class 'numpy.ndarray'&gt;
  training samples  74067 74067
  &lt;class 'numpy.ndarray'&gt; &lt;class 'numpy.ndarray'&gt;
  base samples  166693 166693
  </code></pre>
  
  <p>but the plot does not show up and I get the error</p>
  
  <pre><code>ValueError: x and y must be the same size
  </code></pre>
  
  <p>at</p>
  
  <pre><code>plt.scatter(X_train, y_train, c="k", label="training samples")
  </code></pre>
  
  <p>but as seen in the output, <code>x</code> and <code>y</code> are of the same size and type. What am I doing wrong?</p>