title: Plot Count of Pandas Dataframe with Start_Date and End_Date
body: <p>I am trying to <code>plot</code> a <code>daily follower count</code> for various <code>twitter handles</code>. The result being something like what you see below, but filterable by more than 1 twitter handle:</p>
  
  <p><a href="https://i.stack.imgur.com/EGzBC.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/EGzBC.png" alt="Follower Count"></a></p>
  
  <p>Usually, I would do this by simply appending a new dataset pulled from Twitter to the original table, with the date of the log being pulled. However, this would make me end up with a million lines in just a few days. And it wouldn't allow me to clearly see when a user has dropped off.</p>
  
  <p>As an <code>alternative</code>, after pulling my data from Twitter, I structured my <code>pandas dataframe</code> like this:</p>
  
  <pre><code>Follower_ID          Handles    Start_Date  End_Date
  100                  x          30/05/2017  NaN
  101                  x          21/04/2017  29/05/2017
  201                  y          14/06/2017  NaN
  100                  y          16/06/2017  28/06/2017
  </code></pre>
  
  <p>Where:</p>
  
  <ul>
  <li><code>Handles:</code>are the accounts I am pulling the Followers for</li>
  <li><code>Follower_ID:</code>is the user following an handle</li>
  </ul>
  
  <p>So, for example, if I were<code>Follower_ID 100</code>, I could follow both <code>handle x</code> and <code>handle y</code></p>
  
  <p>I am wondering what would be the best way to prepare the data (<code>pivot</code>, <code>clean through a function</code>, <code>groupby</code>) so that then it can be plotted accordingly. Any ideas?</p>