title: multidimensional hierarchical clustering - python
body: <p>is there something out there that does multidimensional hierarchical clustering?</p>
  
  <p>I have looked in these places:</p>
  
  <ul>
  <li><a href="http://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html" rel="nofollow">http://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html</a></li>
  <li><a href="http://scikit-learn.org/stable/modules/clustering.html" rel="nofollow">http://scikit-learn.org/stable/modules/clustering.html</a></li>
  <li><a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.dendrogram.html#scipy.cluster.hierarchy.dendrogram" rel="nofollow">http://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.dendrogram.html#scipy.cluster.hierarchy.dendrogram</a></li>
  </ul>
  
  <p>but with no success so far</p>
  
  <p>meaning: finding groups same way that was done with 2 dimensions, but with multiple dimensions</p>
  
  <p>some code:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  set_of_values = pd.DataFrame(
      [np.random.rand(10),
       np.random.rand(10),
       np.random.rand(10),
       np.random.rand(10),
       np.random.rand(10),],
       index=['temp differential', 'power differential', 'cost', 'time','output'],
      columns=range(10)).transpose()
  print(set_of_values)
  </code></pre>
  
  <p>I'd like to find all the clusters for ('temp differential', 'power differential', 'cost', 'time','output'). not graphically as it is an hyperplane. ideally with an output like [all the groups]:</p>
  
  <pre><code>GROUP #1: (a,b,c,d,e), (a',b',c',d',e'), ... , (a'',b'',c'',d'',e'') 
  ...
  GROUP #n: ('a,'b,'c,'d,'e), ('a,'b,'c,'d,'e), ... , (''a,''b,''c,''d,''e) 
  </code></pre>
  
  <p>given a threshold on the progressive 'clustering'. is it doable?</p>