input: Write a python function to perform KMeans clustering on a given DataFrame.
  assert perform_kmeans_clustering(df, 3).tolist() == kmeans.labels_.tolist()
  assert perform_kmeans_clustering(df, 3, random_state=0).tolist() == kmeans.labels_.tolist()
  assert len(perform_kmeans_clustering(df, 3)) == len(df)
output: from sklearn.cluster import KMeans
  import pandas as pd
  
  def perform_kmeans_clustering(df, n_clusters, random_state=None):
      kmeans = KMeans(n_clusters=n_clusters, random_state=random_state)
      kmeans.fit(df)
      return pd.Series(kmeans.labels_)