title: How to retrieve the cluster centroids in sic-kit learn's K-means?
body: <p>I'm using this simple script to cluster data using sci-kit learn</p>
  
  <pre><code>from sklearn.cluster import KMeans
  import pandas as pd 
  import matplotlib.pyplot as plt
  X = pd.read_csv('TestData.csv')
  est = KMeans(n_clusters=10)
  Y = pd.DataFrame(est.fit_predict(X))
  frames = [X,Y]
  Out = pd.concat(frames, axis = 1)  
  </code></pre>
  
  <p>This gives me the following output:</p>
  
  <pre><code>   (feat1) (feat2) (cluster ID) 
  0   0.866  1124.182  9
  1   2.078  2688.612  1
  2   0.000     0.000  0
  3   0.000     0.000  0
  4   1.038  1344.306  6
  5   2.388  3090.338  5
  6   0.580   749.456  8
  7   1.556  2016.456  2
  </code></pre>
  
  <p>I want to also display the centroids for each cluster so that the output looks like:</p>
  
  <pre><code>   (feat1) (feat2) (cluster ID) (centroid 1) (centroid 2)  
  0   0.866  1124.182  9
  1   2.078  2688.612  1
  2   0.000     0.000  0
  3   0.000     0.000  0
  4   1.038  1344.306  6
  5   2.388  3090.338  5
  6   0.580   749.456  8
  7   1.556  2016.456  2
  </code></pre>
  
  <p>I tried using est.cluster_centers_ </p>
  
  <p>But that didn't work. </p>
  
  <p>How can I get the correct cluster centers? </p>