用k-means写一段代码

Sure, here is an example code for k-means clustering in Python:

from sklearn.cluster import KMeans
import numpy as np

# Generate some random data
X = np.random.rand(100, 2)

# Initialize the k-means model with 3 clusters
kmeans = KMeans(n_clusters=3)

# Fit the model to the data
kmeans.fit(X)

# Get the cluster labels for each data point
labels = kmeans.predict(X)

# Get the centroids of each cluster
centroids = kmeans.cluster_centers_

This code uses the `KMeans` class from the `sklearn.cluster` module to cluster some random data into 3 clusters. The `fit` method is used to train the model on the data, and the `predict` method is used to get the cluster labels for each data point. Finally, the `cluster_centers_` attribute is used to get the centroids of each cluster.