text: import pandas
  import sklearn.cluster
  import sklearn.metrics
  
  print('Loading clusters...')
  X = pandas.DataFrame({ 'x' : [-2, -1, 1, 2, 3, 4, 5, 7, 8] })
  cs = sklearn.cluster.KMeans(n_clusters = 2, random_state = 0).fit(X)
  
  # Verfiy cluster assignments are correct
  print('\tCluster Assignment:', cs.labels_)
  
  ###
  # Q4.a
  ###
  print('Q4.a')
  
  # Compute sillouette width
  sil = sklearn.metrics.silhouette_score(X, cs.labels_)
  print('\t', sil)
  
  
  ###
  # Q4.c
  ###
  print('Q4.c')
  
  # Compute davies
  dbs = sklearn.metrics.davies_bouldin_score(X, cs.labels_)
  print('\t', dbs)