title: N-gram based dataset Structure for Text Classification in R
body: <p>I want to generate n-grams from a set of user generated sentiments. All statements are placed in a single column in my dataset.</p>
  
  <p>I have been around packages <code>quanteda</code>,  <code>tokenizers</code> and <code>tm</code> for most of my text processing and text mining tasks.</p>
  
  <p>Now my question would be, how do I structure my dataset to be able to use n-grams as part of the features used in learning the model from. Are the tokens placed in separate columns? Or tokens are placed in 1 column and just let classification tasks do their thing?</p>