title: Python/Pandas: counting the number of missing/NaN in each row
body: <p>I've got a dataset with a big number of rows. Some of the values are NaN, like this:</p>
  
  <pre><code>In [91]: df
  Out[91]:
   1    3      1      1      1
   1    3      1      1      1
   2    3      1      1      1
   1    1    NaN    NaN    NaN
   1    3      1      1      1
   1    1      1      1      1
  </code></pre>
  
  <p>And I want to count the number of NaN values in each string, it would be like this:</p>
  
  <pre><code>In [91]: list = &lt;somecode with df&gt;
  In [92]: list
      Out[91]:
       [0,
        0,
        0,
        3,
        0,
        0]
  </code></pre>
  
  <p>What is the best and fastest way to do it?</p>