你能写代码实现随机生成2维坐标点，对点进行聚类，进行K=2,3,4,聚类并用matplot画图吗

当然可以，以下是Python代码实现：

import random
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans

# 随机生成二维坐标点
def generate_points(num):
    points = []
    for i in range(num):
        x = random.uniform(0, 10)
        y = random.uniform(0, 10)
        points.append((x, y))
    return points

# 对点进行聚类
def cluster_points(points, k):
    kmeans = KMeans(n_clusters=k)
    kmeans.fit(points)
    return kmeans.labels_

# 画图
def plot_clusters(points, clusters, k):
    colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
    for i in range(k):
        cluster_points = [points[j] for j in range(len(points)) if clusters[j] == i]
        plt.scatter([p[0] for p in cluster_points], [p[1] for p in cluster_points], c=colors[i])
    plt.show()

# 测试
points = generate_points(100)
for k in range(2, 5):
    clusters = cluster_points(points, k)
    plot_clusters(points, clusters, k)

这段代码会随机生成100个二维坐标点，并对这些点进行K=2,3,4的聚类并用matplotlib画图展示。