title: select by common values in multiple pandas dataframes
body: <p>I'm a newbie to pandas, and suspect this has a simple answer, but it's stumping me right now.  I want to select the rows from multiple dataframes (with same columns) where a value in one column occurs in all of the dataframes.</p>
  
  <p>So if I have the following:</p>
  
  <pre><code>import numpy as np
  import pandas as pd
  
  df1 = pd.DataFrame({'Col1'['Adams','Baker','Cash','Jones','Thomas'],\
                  'Col2': ['A','B','C','D','E'],'Col3':[10,11,12,13,14]})
  df2 = pd.DataFrame({'Col1':['Adams','Cash','Fox','Jones','Johnson'],\
                 'Col2': ['D','E','F','G','H'],'Col3':[40,50,60,70,80]})
  df3 = pd.DataFrame({'Col1': ['Adams','Barns','Jones','Smith','Thomas'],\
                 'Col2':['F','G','J','L','M'],'Col3':[21,21,22,23,24]})
  print df1
  print df2
  print df3
  </code></pre>
  
  <p>Giving:</p>
  
  <pre><code>     Col 1   Col2  Col3
  0    Adams   A    10
  1    Baker   B    11
  2    Cash    C    12
  3   Jones    D    13
  4  Thomas    E    14
    Col1 Col2  Col3
  0    Adams    D    40
  1     Cash    E    50
  2      Fox    F    60
  3    Jones    G    70
  4  Johnson    H    80
     Col1 Col2  Col3
  0   Adams    F    21
  1   Barns    G    21
  2   Jones    J    22
  3   Smith    L    23
  4  Thomas    M    24
  </code></pre>
  
  <p>I want to end up with:</p>
  
  <pre><code>Adams    A     10
  Adams    D     40
  Adams    F     21
  Jones    D     13
  Jones    G     70
  Jones    J     22
  </code></pre>
  
  <p>Is there a succinct way to do this?</p>