title: Pandas: Dropping Duplicate Values But Keeping How Many Values in Another Column
body: <p>I have a dataframe of tweets and I have made a user_table accordingly. I want to see which users are most active.</p>
  <p>I am already able to drop duplicate values with</p>
  <pre class="lang-python prettyprint-override"><code>from collections import Counter
  user_list = user_table['user.id'].tolist()
  user_count = Counter(user_list) # get dictionary count
  user_table.drop_duplicates(subset='user.id', keep = 'first', inplace = True) # drops duplicate values
  </code></pre>
  <p>However I am about to match each id to the appropriate dictionary and assign to list on ordering, turn that into a pandaseries and then assign a column in user_table to that, but I feel like there should be a more streamlined approach</p>