title: More efficient pandas python command to drop Nan rows?
body: <p>I have a DF called TI.  I want to drop rows where BookDate is NaN.  So I run:</p>
  
  <pre><code>TI = TI.dropna(subset=['#Book_Date'])
  </code></pre>
  
  <p>When I run this, the memory gets eaten up for some reason (I'm on a 100GB of RAM machine, and about 50% of the RAM is used to hold TI, when I run that dropna line, it goes to 100% usage and never finished executing the commmand).  Is it making a whole new copy?  TI is a 64 million row dataframe, so it needs to be more efficient. </p>