title: Pandas boolean mask contains NaNs. How to filter?
body: <p>I have this pandas DataFrame bellow:</p>
  <pre><code>    Id                          Guild                                     Test
  0   5c5dc770f920209b94c3def3    72f92390/7f2e/4b41/b53b/393470619eca      True
  1   5c5dc7707d62f8b356457863    596f57d7/c8a9/4b14/aec1/18ef2b9fa940      None
  2   5c5dc770974d1a6d38cffa3a    6a7ad94c/0511/4ef9/8b60/e05158cad03c     False
  3   5c5dc7709809c3452ae07d22    843d9c5f/1f53/4752/a905/0b1de73efab2      None
  4   5c5dc7706c606a2118c4350b    9d63dcc5/1063/49b3/9a90/a854e7eb7398      None
  </code></pre>
  <p><strong>When i tried to apply numpy.where: <br></strong></p>
  <pre><code>pdf['Id'] = np.where(bool(pdf['Test']), pdf['Id'], None)
  </code></pre>
  <p><strong>Also tried using numpy.equal:<br></strong></p>
  <pre><code>pdf['Id'] = np.where(np.equal(pdf['Test'], None), None, pdf['Id'])
  </code></pre>
  <p>Throws me the error:</p>
  <blockquote>
  <p>ValueError: The truth value of a Series is ambiguous. Use a.empty,
  a.bool(), a.item(), a.any() or a.all().</p>
  </blockquote>
  <p>My goal: Apply None to Id columns where Teste is not a valid boolean.</p>
  <p>I've check these similar questions:
  <a href="https://stackoverflow.com/questions/10062954/valueerror-the-truth-value-of-an-array-with-more-than-one-element-is-ambiguous">link One</a> <a href="https://stackoverflow.com/questions/36921951/truth-value-of-a-series-is-ambiguous-use-a-empty-a-bool-a-item-a-any-o">Link Two</a></p>
  <p>Thanks in advance.</p>