title: Pandas standard deviation on one column for subset of rows
body: <p>I'm new to working with Python and Pandas. Currently I'm attempting to create a report that extracts data from an SQL database and using that data in a pandas dataframe. In each row is a server name and date of sample and then sample data per column following that. </p>
  
  <p>I have been able to filter by the hostname using
      df[df['hostname'] == uniquehost]
  df being a variable for the dataframe and uniquehost being a variable for each unique host name.</p>
  
  <p>What I am trying to do next is to obtain the stdev of the other columns although I haven't been capable of figuring this part out. I attempted to use
      df[df['hostname'] == uniquehost].std()</p>
  
  <p>However, this wasn't correct. </p>
  
  <p>Can anyone point me in the appropriate direction to get this figure out? I suspect I'm barking up the wrong tree and there's likely a very easy way to handle this that I haven't encountered yet. </p>
  
  <pre><code>Hostname | Sample Date | CPU Peak | Memory Peak 
  server1 | 08/08/17 | 67.32 | 34.83 
  server1 | 08/09/17 | 34 | 62
  </code></pre>