Hierarchical Clustering using Python on Correlation Coefficient
<p>I have the data in 50 by 50 Matrix that represents the 50 Journals with their correlation. Now, I am trying to plot the graph showing on which clusters those 50 Journals fall based on the data. </p>

<p>1) I prefer to use complete-linkage or Ward's method to do the clusters.
2) I am stuck at where to begin the clustering as the documentation in scikit-learn is too technical for me
3) Could you please help me to give a kick-start? </p>

<p>Thank you very much in advance...</p>

<p>My all data falls between -1 and 1 as it is correlation coefficients.</p>

<p>Example of Data Sample (50*50):</p>

<p>data = [[ 1.          0.49319094  0.58838586 ...,  0.11433441  0.6450184
   0.60842821]</p>

<p>[ 0.49319094  1.          0.39311674 ..., -0.00795401  0.42944597
   0.68855177]</p>

<p>[ 0.58838586  0.39311674  1.         ...,  0.39785574  0.864322
   0.68910632]</p>

<p>..., </p>

<p>[ 0.11433441 -0.00795401  0.39785574 ...,  1.          0.38623474
   0.34228516]</p>

<p>[ 0.6450184   0.42944597  0.864322   ...,  0.38623474  1.          0.65408474]</p>

<p>[ 0.60842821  0.68855177  0.68910632 ...,  0.34228516  0.65408474  1.        ]]</p>