from sklearn cluster import agglomerativeclustering cluster agglomerativeclustering(n_clusters= affinity='euclidean'linkage='ward'cluster fit_predict(xnextplot the cluster with the help of following codeplt scatter( [:, ], [:, ] =cluster labels_cmap='rainbow'the above diagram shows the two clusters from our datapoints example as we understood the concept of dendrograms from the simple example discussed abovelet us move to another example in which we are creating clusters of the data point in pima indian diabetes dataset by using hierarchical clusteringimport matplotlib pyplot as plt import pandas as pd %matplotlib inline import numpy as np from pandas import read_csv path " :\pima-indians-diabetes csvheadernames ['preg''plas''pres''skin''test''mass''pedi''age''class'data read_csv(pathnames=headernamesarray data values array[:, :