title: Calculating means for multiple columns, in different rows in pandas
body: <p>I have a csv file like this:</p>
  
  <pre><code>-Species-    -Strain-       -A-       -B-       -C-       -D-
   Species1    Strain1.1         0.2       0.1       0.1       0.4
   Species1    Strain1.1         0.2       0.7       0.2       0.2
   Species1    Strain1.2         0.1       0.6       0.1       0.3
   Species1    Strain1.1         0.2       0.6       0.2       0.6
   Species2    Strain2.1         0.3       0.3       0.3       0.1
   Species2    Strain2.2         0.6       0.2       0.6       0.2
   Species2    Strain2.2         0.2       0.1       0.4       0.2
  </code></pre>
  
  <p>And I would like to calculate a mean (average) for each unique strain for each of the columns (A-D) how would I go about doing it?</p>
  
  <p>I tried <code>df.groupby(['Strain','Species']).mean().mean(1)</code> but that still seems to give me multiple versions of strains in the resulting dataframe, rather than the means for each columns for each unique strain.</p>
  
  <p>Essentially I would like a mean result for A,B,C &amp; D per strain.</p>
  
  <p>Apologies for being unclear, I'm struggling to get my head around this, and I'm very new to programming!</p>