title: Matplotlib Scatter - ValueError: RGBA sequence should have length 3 or 4
body: <p>I am trying to plot a graph for my features and I keep getting this error:</p>
  
  <pre><code>ValueError: RGBA sequence should have length 3 or 4
  </code></pre>
  
  <p>The code worked perfectly whenever I only had 6 types of shapes but now that i've increased it to 10 it wont work?</p>
  
  <p>If I make <code>c=c</code> with <code>c = np.random.random((100, 4))</code> instead of <code>c=y</code> it works but then every data point has a different colour.</p>
  
  <p>My code is:</p>
  
  <pre><code>features = ["Number of Sides", "Standard Deviation of Number of Sides/Perimeter",
        "Standard Deviation of the Angles", "Largest Angle"]
  
  features1 = ["Label"]
  
  def Build_Data_Set():
  
      data_df = pd.DataFrame.from_csv("AllMixedShapes2.csv")
  
      #This line randomly shuffles the data so that the different types of training data get
      #mixed up randomly to prevent the data being skewed
      data_df = data_df.reindex(np.random.permutation(data_df.index))
      X = np.array(data_df[features].values)
  
      data_df2 = pd.DataFrame.from_csv("AllMixedShapes2.csv")
      y = np.array(data_df2[features1].replace("Circle",0).replace("Equilateral Triangle",1)
               .replace("Right Angle Triangle",2).replace("Acute Triangle",3)
               .replace("Obtuse Triangle",4).replace("Square",5)
               .replace("Parallelogram",6).replace("Rectangle",7)
               .replace("Pentagon",8).replace("Seal",9).values.tolist())
  return X,y
  
  def SVC_Analysis():
  
      test_size = 300
      X,y = Build_Data_Set()
  
      clf = svm.SVC(kernel = 'rbf', C = 1.0)
      clf.fit(X[:test_size],y[:test_size])
  
      correct_count = 0
  
      for x in range(1, test_size+1):
              if clf.predict(X[-x])[0] == y[-x]:
                  correct_count += 1
  
      print("Accuracy:", (correct_count/test_size) * 100.00)
  
  
      data_df = pd.DataFrame.from_csv("AllMixedShapes2.csv")
      X1 = np.array(data_df[features2].values)
      y1 = np.array(data_df[features3].values)
      #w = clf.coef_[0]
      #a = -w[0] / w[1]
      xx = np.linspace(0,5)
      yy = np.linspace(0,185)
  
      h0 = plt.plot(xx,yy, "k-", label="non weighted")
  
      plt.scatter(X1[:, 0],y1, c=y, cmap=plt.cm.Paired)
      plt.ylabel("Maximum Angle (Degrees)")
      plt.xlabel("Number Of Sides")
      plt.title('Shapes')
      plt.legend()
      plt.show()
  
  SVC_Analysis()
  </code></pre>
  
  <p><a href="https://www.dropbox.com/s/kegivh5vvrklopd/AllMixedShapes2.csv?dl=0" rel="noreferrer">My csv file for reference looks like</a></p>
  
  <p>As far as I can tell the problem is to do with <code>c=y, cmap=plt.cm.Paired)</code> but I cant be sure and I cant find a solution.</p>