Python 如何设置初始值？（K-均值聚类）

我想将（2,8）和（8,1）设置为初始赋值 并通过绘图查看两组质心中每一步的变化

你能帮我完成编码吗

import pandas as pd
import numpy as np
from sklearn.cluster import kMeans
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

df = pd.DataFrame(columns=('x','y'))

df.loc[0] = [2,8]
df.loc[1] = [8,1]
df.loc[2] = [1,2]
df.loc[3] = [2,3]
df.loc[4] = [4,2]
df.loc[5] = [7,10]
df.loc[6] = [5,7]
df.loc[7] = [9,7]

df.head(8)

#Scatter Plot
sns.Implot('x','y', data=df, fit_reg = False, scatter_kws={"s":200})
plt.title('kmean plot')
plt.xlabel('x')
plt.ylable('y')

data_points = df.values
kmeans = KMeans(n_clusters=2).fit(data_points)

#Result for clustering
kmeans.labels 
df['cluster_id'] = kmeans.labels
print(df)

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