title: Filter rows from a pandas column binned by pandas.cut()
body: <p>I have a pandas series that I've got from <code>pandas.cut()</code>.</p>
  <p>Given a value 'VALUE' I'd like a boolean series for all the rows whose interval comprises the given value.</p>
  <p>For instance, if  i have a value = 10 I'd like the rows with the bin (8, 12] to assume True and those with the bin (0, 8] assume False.</p>
  <p>I´ve managed to do that using:</p>
  <pre><code>mask = (df['COLUMN'].apply(lambda x: x.left).astype('float64') &lt;= VALUE ) &amp; (df['COLUMN'].apply(lambda x: x.right).astype('float64') &gt;= VALUE )
  </code></pre>
  <p>I feel this is not an efficient way for doing it. Is there any better way for doing so?</p>