title: Searching a Pandas DataFrame column for empty values gives contradictory results
body: <p>I'm trying to clean <a href="https://www.kaggle.com/c/titanic/data" rel="nofollow noreferrer">test data from Kaggle's Titanic dataset</a>, specifically the columns - sex, fare, pclass, and age. In order to do this, I'd like to find out if any of these columns have empty values. I load the data:</p>
  
  <pre><code>import pandas as pd
  test_address = 'path_to_data\test.csv'
  test = pd.read_csv(test_address)
  </code></pre>
  
  <p>When I try to look for empty values in the columns, </p>
  
  <pre><code>True in test['Sex'].isna()
  </code></pre>
  
  <p>outputs True.</p>
  
  <p>However, </p>
  
  <pre><code>test['Sex'].isna().value_counts()
  </code></pre>
  
  <p>outputs</p>
  
  <pre><code>False    418
  Name: Sex, dtype: int64
  </code></pre>
  
  <p>which should mean there aren't any empty values (I could confirm this by visually scanning the csv file). These commands on <code>test['Pclass']</code> have similar outputs. </p>
  
  <p>Why is the 'True in' command giving me the wrong answer?</p>