title: pandas: Multiply MultiIndex DataFrame with Series
body: <p>I have a MultiIndex DataFrame that contains these values:</p>
  
  <pre><code>                      AAPL
             minor          
  2007-09-14 OC     0.024436
  2007-09-15 CC     0.030293
             CO     0.017518
             OC     0.024688
             OO     0.031835
  
  # to_dict():
  
  {'AAPL': {(&lt;Timestamp: 2007-09-14 00:00:00&gt;, 'OC'): 0.024436265475779286,
    (&lt;Timestamp: 2007-09-15 00:00:00&gt;, 'CC'): 0.030293017084353703,
    (&lt;Timestamp: 2007-09-15 00:00:00&gt;, 'CO'): 0.017518449703066673,
    (&lt;Timestamp: 2007-09-15 00:00:00&gt;, 'OC'): 0.024688182799779634,
    (&lt;Timestamp: 2007-09-15 00:00:00&gt;, 'OO'): 0.031834725061579666}}
  </code></pre>
  
  <p>--</p>
  
  <p>and a Series that contains these values:</p>
  
  <pre><code>CC    15.874508
  CO    18.590320
  OC    30.503468
  OO    15.874508
  
  # to_dict():
  
  {'CC': 15.874507866387544,
   'CO': 18.590320061795602,
   'OC': 30.503467646507644,
   'OO': 15.874507866387544}
  </code></pre>
  
  <p>I'd like to multiply all of the minor index CC values by the CC value in the Series, and the same with the other values.  I saw another question on here that gave me the .mul method, but when I try that, even with the level='minor', it tells me:</p>
  
  <blockquote>
    <p>TypeError: can only call with other hierarchical index objects</p>
  </blockquote>
  
  <p>I've unstacked the minor index to make it columns, and specified level='minor', axis='columns' with the same result.</p>
  
  <p>Finally, the end result is to be able to run this same calculation on a DataFrame where the major columns are several equities -- in that instance, would .mul() work against each equity as well?</p>
  
  <p>Thanks for your assistance!</p>