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