title: Seaborn.clustermap : cluster rows and columns using different metrics
body: <p>I was trying to generate a clustermap using one of the Seaborn functions.
  Currently, it allows me to use the same metric (Pearson, Euclidean etc.) for rows and columns, but remains difficult for using different metrics, unlike MATLAB's clustergram.</p>
  <p>Based on <a href="https://seaborn.pydata.org/generated/seaborn.clustermap.html" rel="nofollow noreferrer">this</a>,</p>
  <blockquote>
  <p>To use different metrics (or methods) for rows and columns, you may construct each linkage matrix yourself and provide them as {row,col}_linkage.</p>
  </blockquote>
  <p>But does anyone know how to do that?</p>