title: Count rows satisfying "less than" filter for sequence of values
body: <p>I have a dataset with a bunch of times. Let's say I wanted to create a summary table that counts number of rows satisfying &quot;less than&quot; filter for a sequence of values, say [number of rows with time &lt; 6, number of rows with time &lt; 7, etc.]</p>
  <p>Example dataset:</p>
  <pre><code>data.frame(personId = c(&quot;2009ZEMD01&quot;, &quot;2012PARK03&quot;, &quot;2017VILL41&quot;, &quot;2010WEYE01&quot;, &quot;2016KOLA02&quot;, &quot;2012PONC02&quot;), 
             average = c(553, 559, 598, 606, 612, 613))
  </code></pre>
  <p>This was my solution using <code>sapply</code>:</p>
  <pre><code>  tibble(time = 6:15, 
           count = sapply(time, function(t) best_3x3_solvers %&gt;% filter(average/100 &lt; t) %&gt;% nrow)) 
  </code></pre>
  <p>The result:</p>
  <pre><code>&gt; solvers_under
  # A tibble: 10 x 2
      time count
     &lt;int&gt; &lt;int&gt;
   1     6     3
   2     7    48
   3     8   274
   4     9   840
   5    10  1952
   6    11  3792
   7    12  6269
   8    13  9459
   9    14 13204
  10    15 17274
  </code></pre>
  <p>The code is not too long but is there a method using more tidyverse tools without <code>*apply</code>? Maybe <code>summarize</code> with <code>n()</code>.</p>