title: R - Comparing differently sized data frames
body: <p>I have two data frames of volume-by-date. They're both the same data, but one is filtered. I'd like to plot a trendline of the ratio between filtered data and non-filtered data on any given day—but am having a hugely hard time molding the data frames so that they're comparable. Here's an example:</p>
  
  <pre><code>unFiltered &lt;- data.frame(date = c("01-01-2015", "01-01-2015", "01-02-2015"), item = c("item1", "item2", "item1"), volume = c(100, 100, 50))
  
  filtered &lt;- data.frame(date = c("01-01-2015", "01-03-2015"), item = c("item1", "item1"), volume = c(10, 40))
  </code></pre>
  
  <p>From these data sets, I'd like to construct a third data set that is "The percentage of unfiltered item-volume that is being filtered". That is, I want a data frame that will look like this:</p>
  
  <pre><code>    date          item    percentage
  1 "01-01-2015"    item1   .1
  2 "01-01-2015"    item2    0
  3 "01-02-2015"    item1    0
  4 "01-02-2015"    item2    0
  5 "01-03-2015"    item1   .8
  6 "01-03-2015"    item2    0
  </code></pre>
  
  <p>(Note: Neither data frame has 6 entries—but the resulting data frame has unique values of <code>item</code> <em>and</em> unique values of <code>date</code>.)</p>
  
  <p>Anyone have any ideas? I've been stuck on this for ~2 hours, fumbling around with for loops, merging, joins, manually creating data frames, etc. If anyone has a solution, would you mind explaining what's going on in said solution, too? (I still kind of suck at R, and often times I read code that someone writes without having any idea why it actually works).</p>