title: Efficiently check if value is present in any of given ranges
body: <p>I have two pandas DataFrame objects:</p>
  
  <ul>
  <li><p><code>A</code> contains <code>'start'</code> and <code>'finish'</code> columns</p></li>
  <li><p><code>B</code> has column <code>'date'</code></p></li>
  </ul>
  
  <p>The goal is to efficiently create a boolean mask indicating if <code>date</code> is in <code>[start, finish]</code> interval</p>
  
  <p>Naive iterating taking too much time, I guess there is a method to do that  faster</p>
  
  <p>UPDATE:
  <code>A</code> and <code>B</code> have <strong>different number of rows</strong></p>
  
  <p>UPDATE2: 
  Sample:</p>
  
  <pre><code>A
      | start     | finish    |
      |-------    |--------   |
      | 1         | 3         |
      | 50        | 83        |
      | 30        | 42        |
  
  B
      | date      | 
      |-------    |
      | 31        | 
      | 20        | 
      | 2.5       |
      | 84        |
      | 1000      |
  
  Output:
              | in_interval | 
              |-------    |
              | True      | 
              | False     | 
              | True      |
              | False     |
              | False     |
  </code></pre>
  
  <p>P.S. I have my data in datetime format but I guess that the solution will not differ from one for numbers</p>