k-means clustering 1d data

kmeans.py

from sklearn.cluster import KMeans
import numpy as np

data = np.array([101, 107, 106, 199, 204, 205, 207, 306, 310, 312, 312, 314, 317, 318, 380, 377, 379, 382, 466, 469, 471, 472, 557, 559, 562, 566, 569])

kmeans = KMeans(n_clusters=5).fit(data.reshape(-1,1))
kmeans.predict(data.reshape(-1,1))

# array([4, 4, 4, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 3,
#       3, 3, 3, 3], dtype=int32)

kmeans.cluster_centers_

#array([[ 337.        ],
#       [ 469.5       ],
#       [ 203.75      ],
#       [ 562.6       ],
#       [ 104.66666667]])