title: How to count nan values in a pandas DataFrame?
body: <p>What is the best way to account for (not a number) nan values in a pandas DataFrame?</p>
  
  <p>The following code:</p>
  
  <pre><code>import numpy as np
  import pandas as pd
  dfd = pd.DataFrame([1, np.nan, 3, 3, 3, np.nan], columns=['a'])
  dfv = dfd.a.value_counts().sort_index()
  print("nan: %d" % dfv[np.nan].sum())
  print("1: %d" % dfv[1].sum())
  print("3: %d" % dfv[3].sum())
  print("total: %d" % dfv[:].sum())
  </code></pre>
  
  <p>Outputs:</p>
  
  <pre><code>nan: 0
  1: 1
  3: 3
  total: 4
  </code></pre>
  
  <p>While the desired output is:</p>
  
  <pre><code>nan: 2
  1: 1
  3: 3
  total: 6
  </code></pre>
  
  <p>I am using pandas 0.17 with Python 3.5.0 with Anaconda 2.4.0.</p>