title: Using psutil.Process.memory_info memory usage differs from Pandas.memory_usage
body: <p>I'm profiling a program that makes use of <code>Pandas</code> to process some CSVs. I'm using <code>psutil's Process.memory_info</code> to report the Virtual Memory Size (vms) and the Resident Set Size (rss) values. I'm also using Pandas <code>DataFrame.memory_usage (df.memory_usage().sum())</code> to report the size of my <code>dataframes</code> in memory.</p>
  
  <p>There's a conflict between the reported <code>vms</code> and <code>df.memory_usage</code> values, where Pandas is reporting more memory just for the <code>dataframe</code> than the <code>Process.memory_info</code> call is reporting for the whole (single-threaded) process.</p>
  
  <p>For example:</p>
  
  <blockquote>
    <ul>
    <li>rss: 334671872 B</li>
    <li>vms: 663515136 B</li>
    <li>df.memory_usage().sum(): 670244208 B</li>
    </ul>
  </blockquote>
  
  <p>The <code>Process.memory_info</code> call is made immediately after the <code>memory_usage</code> call. My expected result was that <code>df.memory_usage &lt; vms</code> at all times, but this doesn't hold up. I assume I'm misinterpreting the meaning of the <code>vms</code> value?</p>