title: How to iterate over pandas multiindex dataframe using index
body: <p>I have a data frame df which looks like this. Date and Time are 2 multilevel index</p>
  <pre><code>                           observation1   observation2
  date          Time                             
  2012-11-02    9:15:00      79.373668      224
                9:16:00      130.841316     477
  2012-11-03    9:15:00      45.312814      835
                9:16:00      123.776946     623
                9:17:00      153.76646      624
                9:18:00      463.276946     626
                9:19:00      663.176934     622
                9:20:00      763.77333      621
  2012-11-04    9:15:00      115.449437     122
                9:16:00      123.776946     555
                9:17:00      153.76646      344
                9:18:00      463.276946     212
  </code></pre>
  <p>I want to run some complex process over daily data block.</p>
  <p>Pseudo code would look like</p>
  <pre><code> for count in df(level 0 index) :
       new_df = get only chunk for count
       complex_process(new_df)
  </code></pre>
  <p>So, first of all, I could not find a way to access only blocks for a date</p>
  <pre><code>2012-11-03    9:15:00      45.312814      835
                9:16:00      123.776946     623
                9:17:00      153.76646      624
                9:18:00      463.276946     626
                9:19:00      663.176934     622
                9:20:00      763.77333      621
  </code></pre>
  <p>and then send it for processing. I am doing this in for loop as I am not sure if there is any way to do it without mentioning exact value of level 0 column. I did some basic search and found  <code>df.index.get_level_values(0)</code>, but it returns all the values and that causes loop to run multiple times for a given day. I want to create a Dataframe per day and send it for processing.</p>