title: Understanding Representation of Vector Column in Spark SQL
body: <p>Before I used VectorAssembler() to consolidate some OneHotEncoded categorical features... My data frame looked like so :</p>
  
  <pre><code>|  Numerical|  HotEncoded1|   HotEncoded2
  |  14460.0|    (44,[5],[1.0])|     (3,[0],[1.0])|
  |  14460.0|    (44,[9],[1.0])|     (3,[0],[1.0])|
  |  15181.0|    (44,[1],[1.0])|     (3,[0],[1.0])|
  </code></pre>
  
  <p>The first column is a numerical column and the other two columns represent the transformed data set for OneHotEncoded categorical features. After applying VectorAssembler(), my output becomes: </p>
  
  <pre><code>[(48,[0,1,9],[14460.0,1.0,1.0])]
  [(48,[0,3,25],[12827.0,1.0,1.0])]
  [(48,[0,1,18],[12828.0,1.0,1.0])]
  </code></pre>
  
  <p>I am unsure of what these numbers mean and cannot make sense of this transformed data set. Some clarification on what this output means would be great!</p>