title: How can sklearn select categorical features based on feature selection
body: <p>My question is i want to run feature selection on the data with several categorical variables. I have used <code>get_dummies</code> in <code>pandas</code> to generate all the sparse matrix for these categorical variables. My question is how sklearn knows that one specific sparse matrix actually belongs to one feature and select/drop them all? For example, I have a variable called city. There are New York, Chicago and Boston three levels for that variable, so the sparse matrix looks like:</p>
  
  <p><code>[1,0,0]
   [0,1,0]
   [0,0,1]
  </code>
   How can I inform the sklearn that in these three "columns" actually belong to one feature, which is city and won't end up with choosing New York, and delete Chicago and Boston?</p>
  
  <p>Thank you so much!</p>