title: How to combine numeric and text data in a scikit dataset
body: <p>I have some data like:</p>
  
  <pre><code>name    | cost
  -----------------
  milk    | 1.20
  butter  | 3.50
  eggs    |  .99
  </code></pre>
  
  <p>I'd like to be able to group these by both name and price (e.g., "skim milk" is related to "whole milk" and five things that are $2.99 would be scored as similar) using one of SciKit's clustering modules, like <a href="http://scikit-learn.org/stable/modules/clustering.html#k-means" rel="nofollow noreferrer">kmeans</a>.  </p>
  
  <p>I know I have to turn the names into numbers, which I'm doing using the <a href="http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.HashingVectorizer.html" rel="nofollow noreferrer"><code>HashingVectorizer</code></a>, which gives me a sparse matrix.  However, at that point, I'm not sure how to combine that with the costs column.  The examples I've seen take the output of HashingVectorizer and feed it straight into <code>kmeans.fit</code>.  </p>
  
  <p>Can someone give (or point me towards) an example that uses text data + at least one other column?</p>