title: pandas groupby for multiple data frames/files at once
body: <p>I have multiple huge tsv files that I'm trying to process using pandas. I want to group by 'col3' and 'col5'. I've tried this:</p>
  
  <pre><code>import pandas as pd
  df = pd.read_csv('filename.txt', sep = "\t")
  g2 = df.drop_duplicates(['col3', 'col5'])
  g3 = g2.groupby(['col3', 'col5']).size().sum(level=0)
  print g3
  </code></pre>
  
  <p>It works fine so far and prints an output like this:</p>
  
  <pre><code>yes 2
  no  2
  </code></pre>
  
  <p>I'd like to be able to aggregate the output from multiple files, i.e., to be able to group by these two columns in all the files at once and print one common output with total number of occurrences of 'yes' or 'no' or whatever that attribute could be. In other words, I'd now like to use groupby on multiple files at once. And if a file doesn't have one of these columns, it should be skipped and should go to the next file.</p>