title: for loop over 20 data frames on each day simultaneously
body: <p>I have the following data structure (still subject to changes):</p>
  
  <pre><code>pp = ([Pair1, Pair2, Pair3, ..., Pair25])
  </code></pre>
  
  <p>Each Pair has has the following format: </p>
  
  <pre><code> &lt;class 'pandas.core.frame.DataFrame'&gt;
   DatetimeIndex: 2016 entries, 2005-09-19 00:00:00 to 2013-09-12 00:00:00
   Data columns (total 2 columns):
   CA      2016  non-null values
   Na      2016  non-null values
  </code></pre>
  
  <p>I have lots of functions which need to be applied on each day for each DataFrame. However, the For-Loop may not run step-by-step such as for Pair1, Pair2, Pair3. The For-loop should rather run each day, for example: </p>
  
  <pre><code> 2005-09-19: do function for each pair!
   2005-09-20  and continue
   2005-09-21 
   2005-09-22 
  </code></pre>
  
  <p>Is there a way to do that or do I need to completely change my data structure as well as codes?</p>
  
  <p><strong>Update 1</strong></p>
  
  <p>This where I am right now, however, is it efficient?</p>
  
  <pre><code>for i in range(len(ps[1])):
      for row in ps:
      print row[i:i+1]
  
  
                   A      C               DE
  Date                                       
  2005-09-19 -0.600021  4.649857            3
                   A     G                DE
  Date                                      
  2005-09-19 -0.600021  6.39693     0.105716
                   A     W                DE
  Date                                       
  2005-09-19 -0.600021  6.950815            5
                   A      C               DE
  Date                                      
  2005-09-20 -0.59711  4.637831            3
                   A      G               DE
  Date                                       
  2005-09-20 -0.59711  6.396263     0.109079
                   A     W                 DE
  Date                                      
  2005-09-20 -0.59711  6.951772            5
                   A      C                DE
  Date                                       
  2005-09-21 -0.594207  4.641213            3
                   A     G                 DE
  Date                                          
  2005-09-21 -0.594207  6.40059     0.109055
                   A     W                DE
  Date                                       
  2005-09-21 -0.594207  6.955593            5
  </code></pre>