title: 3-dimensional array to dataframe in R for optimized boxplotting
body: <p>I am handling a slightly large set of data (dimensions 360,25,3): dimensions correspond to (event_severity,zone,<strong>model</strong>) respectively. I also have a similar dataframe for another <em><strong>time window</strong></em></p>
  <p>I imagine my data to be organized into three stacked matrices (one per <strong>model</strong>), with each column containing all the event_severities.</p>
  <p>I need to perform two operations on the above matrix:</p>
  <ol>
  <li><p>remove all events whose event_severity = 0
  The tricky part here is that every zone (column) has a different number of 0's, so removing them results in columns of different length. I don't know if this can be an issue for the rest of my task, but i wold like to know how to work around this</p>
  </li>
  <li><p>plot a grouped boxplot of the severities for each zone (25 different plots) grouping them by <strong>model</strong> and comparing the two different <em><strong>time windows</strong></em></p>
  </li>
  </ol>
  <p>The final result I am expecting looks more or less like this:</p>
  <p><a href="https://i.stack.imgur.com/MSzlK.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/MSzlK.png" alt="expected result" /></a></p>
  <p>The variables to be box-plotted are the event_severities (i am computing their statistics). I would like to have a plot comparing the severities of a given zone, for three different <strong>models</strong>, between two separate <em><strong>time windows</strong></em></p>
  <p>Note #1: browsing through R-boxplot guides on the internet, i thought putting my data in a dataframe could help. However, by using as.data.frame on my (360,25,3) array transforms it into a 360 observation-75 variables dataframe, which i have a hard time interpreting.</p>
  <p>Note#2: if you could walk me through the plotting instruction that would be greatly appreciated</p>