title: Normalising a data set with irregular intervals in Python
body: <p>I have some data in Python that eventually gets plotted on a graph (Highcharts) the issue is that intervals between data points on the x axis (time) are not regular. While accurate this makes the graph seem a bit erratic, visually.</p>
  
  <p>The data is in the following format:</p>
  
  <pre><code>data = {"points": [[1335360000, 1335361920, 93374739787], [1335361920, 1335447840, 11738851087.0]......]} 
  </code></pre>
  
  <p>That is: timestamp from, timestamp to, value</p>
  
  <p>What I need to do is modify the data so that it normalises to the lowest frequency/longest time interval so that it will appear consistant when plotted on a graph.</p>
  
  <p>Are there any ideas on the most efficient way to do this?</p>
  
  <h2>Update</h2>
  
  <p>I can't really use any 3rd party libaries in this situation.</p>
  
  <p>Graphs usually are rendered like this, appearing more jagged where the data points are closer together:</p>
  
  <p><a href="https://i.stack.imgur.com/nFB9U.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/nFB9U.png" alt="Graph Example"></a>
  </p>