input: def kmeans(k, data): 
      """
      Perform k-means clustering on data
      >>> kmeans(2, np.array([[1, 1], [2, 1], [4, 3], [5, 4]]))
      (array([0, 0, 1, 1]), array([[1.5, 1. ],
         [4.5, 3.5]]))
      """
output:     import numpy as np
      from sklearn.cluster import KMeans
  
      kmeans = KMeans(n_clusters=k).fit(data)
      labels = kmeans.labels_
      centers = kmeans.cluster_centers_
      return labels, centers