title: What is the most suitable/efficient pandas data type for IDs?
body: <p>Probably obvious, but just wanted to confirm:</p>
  <p>What would be the best suited data type for a numerical ID in pandas?</p>
  <p>Let's say that I have a sequential numerical ID type <code>user_id</code>, which would be better:</p>
  <ul>
  <li>an <code>int64</code> type (that would seem to be the most obvious choice given the numerical representation of the field)</li>
  <li>a <code>category</code> type (which might make more sense, given that the ID is not to be used for actual numerical operations, but rather as a unique identifier)</li>
  </ul>
  <p>Same question for characters-based IDs, would it be better to use an <code>object</code> or a <code>category</code> type?</p>
  <p>I would be tempted to use the <code>category</code> data type (thinking there might be performance benefits, as I would imagine these categories are somehow optimised/hashed/indexed for performance), but I was wondering whether this data type is more suited for a more limited subset of distinct values than the possible 100's of thousands unique user_ids I might have in my dataset.</p>
  <p>Thanks!</p>