title: Distribution with Seaborn
body: <p>I have a pandas dataframe that is composed like this:</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>User_id</th>
  <th>Calls</th>
  <th>Index</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>7A</td>
  <td>8</td>
  <td>19-05-2020</td>
  </tr>
  <tr>
  <td>10B</td>
  <td>5</td>
  <td>19-05-2020</td>
  </tr>
  <tr>
  <td>7A</td>
  <td>2</td>
  <td>20-05-2020</td>
  </tr>
  <tr>
  <td>10B</td>
  <td>6</td>
  <td>20-05-2020</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>With in index the dates and times at which they make their calls even if here I put it on the right under pandas say that the dates are the index on the left.</p>
  <p>I would like to make the distribution of the users of their number of calls that they make in the year.</p>
  <p>Currently there are more than 400 different users so I will not do all of them only those who have the largest number of calls that I find easily with this: <code>ret.groupby(['user_id'])['calls'].sum().sort_values(ascending=False).head(10)</code></p>
  <p>I try to make a loop that takes the first 10 users who have the most calls and makes their distribution of calls in the year (so we have on the x-axis the months of the year written in number or not, on the y-axis the density or the number of calls, and we would have a title to say of which users we made the graph)</p>
  <p>How can I do it?</p>