input: Write a python function to perform KMeans clustering on given x and y points and return the cluster labels.
  assert cluster_data([1, 2, 3, 4, 5], [1, 4, 3, 2, 5])==[1, 2, 0, 2, 1]
  assert cluster_data([5, 6, 7, 8, 9], [10, 11, 12, 13, 14])==[0, 0, 0, 1, 1]
  assert cluster_data([1, 0, 5, 6, 9], [2, 3, 1, 5, 4])==[1, 1, 0, 0, 2]
output: def cluster_data(x, y, n_clusters=3):
      from sklearn.cluster import KMeans
      import numpy as np
      
      points = np.array(list(zip(x, y)))
      kmeans = KMeans(n_clusters=n_clusters, random_state=0).fit(points)
      
      return kmeans.labels_.tolist()