title: How to filter by sub-level index in Pandas
body: <p>I have a 'df' which have a multilevel index (STK_ID,RPT_Date)</p>
  
  <pre><code>                       sales         cogs     net_pft
  STK_ID RPT_Date                                      
  000876 20060331          NaN          NaN         NaN
         20060630    857483000    729541000    67157200
         20060930   1063590000    925140000    50807000
         20061231    853960000    737660000    51574000
         20070331  -2695245000  -2305078000  -167642500
         20070630   1146245000   1050808000   113468500
         20070930   1327970000   1204800000    84337000
         20071231   1439140000   1331870000    53398000
         20080331  -3135240000  -2798090000  -248054300
         20080630   1932470000   1777010000   133756300
         20080930   1873240000   1733660000    92099000
  002254 20061231 -16169620000 -15332705000  -508333200
         20070331   -763844000   -703460000    -1538000
         20070630    501221000    289167000   118012200
         20070930    460483000    274026000    95967000
  </code></pre>
  
  <p>How to write a command to filter the rows whose 'RPT_Date' contains '0630' (which is the Q2 report) ? the result should be :</p>
  
  <pre><code>                       sales         cogs     net_pft
  STK_ID RPT_Date                                      
  000876 20060630    857483000    729541000    67157200
         20070630   1146245000   1050808000   113468500
         20080630   1932470000   1777010000   133756300
  002254 20070630    501221000    289167000   118012200
  </code></pre>
  
  <p>I am trying to use <code>df[df['RPT_Date'].str.contains('0630')]</code>, but Pandas refuses to work as <code>'RPT_Date'</code> is not a column but a sub_level index.</p>
  
  <p>Thanks for your tips ...</p>