title: strings as features in decision tree/random forest
body: <p>I am new to machine learning!</p>
  
  <p>Right now I am doing some problems on application of decision tree/random forest. I am trying to fit a problem which has numbers as well as strings (such as country name) as features. Now the library, scikit-learn takes only numbers as parameters, but I want to inject the strings as well as they carry significant amount of knowledge.</p>
  
  <p>How do I handle such scenario, I can convert string to numbers by some mechanism such as hashing in python. But I would like to know the best practice on how strings are handled in decision tree problems.</p>