title: How to handle extremely large data sets in pandas
body: <p>I need to merge 5 collections in a MongoDB on a couple of field names &amp; return it as a CSV file.  I can read the collections into pandas using the <code>from_records</code> method no problem &amp; merge a subset of these using <code>pd.merge</code> but the issue is each data frame I want to merge has 20,000+ columns &amp; 100,000+ rows.  The merging process is obviously extremely slow due to size.  </p>
  
  <p>I've never dealt with data on this order of magnitude -- what are some ways I can speed up this process?  Maybe pandas isn't the right tool to use at this point?     </p>