我正尝试使用plotly express来执行聚类（即，聚类和质心），如这里突出显示的那样。按照这个例子，我能够表示不同的聚类。但是，我似乎很难找到关于如何使用plotly express来表示生成的聚类上的聚类质心的信息。
数据集：

column_a,column_b,column_c,column_d
5.1,3.5,1.4,0.2
4.9,3.0,1.4,0.2
4.7,3.2,1.3,0.2
4.6,3.1,1.5,0.2
5.0,3.6,1.4,0.2
5.4,3.9,1.7,0.4
4.6,3.4,1.4,0.3
5.0,3.4,1.5,0.2
4.4,2.9,1.4,0.2
4.9,3.1,1.5,0.1
5.4,3.7,1.5,0.2
4.8,3.4,1.6,0.2
4.8,3.0,1.4,0.1
4.3,3.0,1.1,0.1
5.8,4.0,1.2,0.2
5.7,4.4,1.5,0.4
5.4,3.9,1.3,0.4
5.1,3.5,1.4,0.3
5.7,3.8,1.7,0.3
5.1,3.8,1.5,0.3
5.4,3.4,1.7,0.2
5.1,3.7,1.5,0.4
4.6,3.6,1.0,0.2
5.1,3.3,1.7,0.5
4.8,3.4,1.9,0.2
5.0,3.0,1.6,0.2
5.0,3.4,1.6,0.4
5.2,3.5,1.5,0.2
5.2,3.4,1.4,0.2
4.7,3.2,1.6,0.2
4.8,3.1,1.6,0.2
5.4,3.4,1.5,0.4
5.2,4.1,1.5,0.1
5.5,4.2,1.4,0.2
4.9,3.1,1.5,0.1
5.0,3.2,1.2,0.2
5.5,3.5,1.3,0.2
4.9,3.1,1.5,0.1
4.4,3.0,1.3,0.2
5.1,3.4,1.5,0.2
5.0,3.5,1.3,0.3
4.5,2.3,1.3,0.3
4.4,3.2,1.3,0.2
5.0,3.5,1.6,0.6
5.1,3.8,1.9,0.4
4.8,3.0,1.4,0.3
5.1,3.8,1.6,0.2
4.6,3.2,1.4,0.2
5.3,3.7,1.5,0.2
5.0,3.3,1.4,0.2
7.0,3.2,4.7,1.4
6.4,3.2,4.5,1.5
6.9,3.1,4.9,1.5
5.5,2.3,4.0,1.3
6.5,2.8,4.6,1.5
5.7,2.8,4.5,1.3
6.3,3.3,4.7,1.6
4.9,2.4,3.3,1.0
6.6,2.9,4.6,1.3
5.2,2.7,3.9,1.4
5.0,2.0,3.5,1.0
5.9,3.0,4.2,1.5
6.0,2.2,4.0,1.0
6.1,2.9,4.7,1.4
5.6,2.9,3.6,1.3
6.7,3.1,4.4,1.4
5.6,3.0,4.5,1.5
5.8,2.7,4.1,1.0
6.2,2.2,4.5,1.5
5.6,2.5,3.9,1.1
5.9,3.2,4.8,1.8
6.1,2.8,4.0,1.3
6.3,2.5,4.9,1.5
6.1,2.8,4.7,1.2
6.4,2.9,4.3,1.3
6.6,3.0,4.4,1.4
6.8,2.8,4.8,1.4
6.7,3.0,5.0,1.7
6.0,2.9,4.5,1.5
5.7,2.6,3.5,1.0
5.5,2.4,3.8,1.1
5.5,2.4,3.7,1.0
5.8,2.7,3.9,1.2
6.0,2.7,5.1,1.6
5.4,3.0,4.5,1.5
6.0,3.4,4.5,1.6
6.7,3.1,4.7,1.5
6.3,2.3,4.4,1.3
5.6,3.0,4.1,1.3
5.5,2.5,4.0,1.3
5.5,2.6,4.4,1.2
6.1,3.0,4.6,1.4
5.8,2.6,4.0,1.2
5.0,2.3,3.3,1.0
5.6,2.7,4.2,1.3
5.7,3.0,4.2,1.2
5.7,2.9,4.2,1.3
6.2,2.9,4.3,1.3
5.1,2.5,3.0,1.1
5.7,2.8,4.1,1.3
6.3,3.3,6.0,2.5
5.8,2.7,5.1,1.9
7.1,3.0,5.9,2.1
6.3,2.9,5.6,1.8
6.5,3.0,5.8,2.2
7.6,3.0,6.6,2.1
4.9,2.5,4.5,1.7
7.3,2.9,6.3,1.8
6.7,2.5,5.8,1.8
7.2,3.6,6.1,2.5
6.5,3.2,5.1,2.0
6.4,2.7,5.3,1.9
6.8,3.0,5.5,2.1
5.7,2.5,5.0,2.0
5.8,2.8,5.1,2.4
6.4,3.2,5.3,2.3
6.5,3.0,5.5,1.8
7.7,3.8,6.7,2.2
7.7,2.6,6.9,2.3
6.0,2.2,5.0,1.5
6.9,3.2,5.7,2.3
5.6,2.8,4.9,2.0
7.7,2.8,6.7,2.0
6.3,2.7,4.9,1.8
6.7,3.3,5.7,2.1
7.2,3.2,6.0,1.8
6.2,2.8,4.8,1.8
6.1,3.0,4.9,1.8
6.4,2.8,5.6,2.1
7.2,3.0,5.8,1.6
7.4,2.8,6.1,1.9
7.9,3.8,6.4,2.0
6.4,2.8,5.6,2.2
6.3,2.8,5.1,1.5
6.1,2.6,5.6,1.4
7.7,3.0,6.1,2.3
6.3,3.4,5.6,2.4
6.4,3.1,5.5,1.8
6.0,3.0,4.8,1.8
6.9,3.1,5.4,2.1
6.7,3.1,5.6,2.4
6.9,3.1,5.1,2.3
5.8,2.7,5.1,1.9
6.8,3.2,5.9,2.3
6.7,3.3,5.7,2.5
6.7,3.0,5.2,2.3
6.3,2.5,5.0,1.9
6.5,3.0,5.2,2.0
6.2,3.4,5.4,2.3
5.9,3.0,5.1,1.8

到目前为止，这是我所尝试的：

import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
import plotly.express as px
from mpl_toolkits.mplot3d import Axes3D
import streamlit as st

df = pd.read_csv('iris.csv')
df_columns = ['column_a', 'column_b', 'column_c']

kmeans = KMeans(n_clusters=3, init = 'k-means++', max_iter=200)
km = kmeans.fit(df[df_columns])
centroids = km.cluster_centers_
cluster_labels = km.labels_
df['cluster'] = pd.Series(cluster_labels, index=df.index)

fig=px.scatter_3d(df, color=cluster_labels, labels={'color': 'cluster'})
#add code for the centroids
st.plotly_chart(fig)

使用matplotlib可以很容易地得到如下结果，但是需要使用plotly express中的scatter_3d

fig=plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(df.iloc[:, 0].values, df.iloc[:, 1].values, df.iloc[:, 2].values, c=cluster_labels , cmap='viridis')
ax.scatter(centroids[:, 0], centroids[:, 1], centroids[:, 2],s = 20, c = 'black', marker='*')

如何使用plotly express的px.scatter_3d（）表示聚类中心