title: Preparation of categorical data for hierarchical clustering
body: <p>I would like to use R to perform a hierarchical clustering of data that looks like this:</p>
  
  <pre><code>     L1   L2   L3
  W1   p    pr   r
  W2   p    NA   r
  </code></pre>
  
  <p>which is supposed to mean that L2 shares feature W1 with both L1 and L3, while feature W2 is present in L1 and L3, but with a different value, and missing from L2. (<em>edit</em> L’s are languages, W’s are stems of words in these languages, and the values (p, r, etc.) describe how these words can be derived in the specific language. I believe that a word’s being derived in the same way in different languages might suggest common origin. When it's missing, it's not clear: it might mean something, or my sources might be incomplete, but I guess I'll have to cautiously assume the first option. The eventual goal is to classify languages by what stems are present in them, and how they behave. <em>end edit</em>)</p>
  
  <p>Can you please explain how I can transform this data so as to be able to perform classification on them, and advise on what similarity index I should use?</p>