kmeans clustering python
There are coordinates that I want to cluster. The result of clustering using the kmeans
[[0, 107], [0, 108], [0, 109], [0, 115], [0, 116],
[0, 117], [0, 118], [0, 125], [0, 126], [0, 127],
[0, 128], [0, 135], [0, 136], [0, 194], [0, 195],
[1, 107], [1, 108], [1, 109], [1, 110], [1, 114],
[1, 115], [1, 116], [1, 117], [1, 118], [1, 119]...]

The result of clustering using the kmeans
from sklearn.cluster import KMeans
num_clusters = 9
km = KMeans(n_clusters=num_clusters)
km_fit = km.fit(nonzero_pred_sub)

&gt;&gt;&gt;array([7, 7, 7, 1, 1, 1, 1, 5, 5, 5, 5, 3, 3, 0, 0, 7, 7, 7, 7, 1, 1, 1,
   1, 1, 1, 5, 5, 5...]

I want to know the coordinates of i-th cluster
for example, i need elements of 1st cluster and i can assume [0, 107], [0, 108], [0, 109] was clustered into the 7-th cluster.
How can i get coordinates from cluster?

I assume you want the coordinates affected to the 7th cluster. You can do so by storing you result in a dictionary :
from sklearn.cluster import KMeans
km = KMeans(n_clusters=9)
km_fit = km.fit(nonzero_pred_sub)

d = dict() # dictionary linking cluster id to coordinates
for i in range(len(km_fit)):
  cluster_id = km_fit[i]

  if cluster_id not in d:
    d[cluster_id] = []
    
  d[cluster_id].append(nonzero_pred_sub[i])

# that way you can access the 7th cluster coordinates like this
d[7]

&gt;&gt;&gt; [[0, 107], [0, 108], [0, 109], [1, 107], [1, 108], [1, 109], [1, 110], ...]

To remove the &quot;if&quot; section in the loop, you can try looking into defaultdict objects.
You can also surely manage that with pandas dataframes to make manipulating more complex results easier.
If I misunderstood you question, and what you want is the coordinates of the center of the i-th cluster, you can get this by calling km_fit.cluster_centers_[i] (cf. doc).
