title: What is the most efficient way to join multiple tables with the same index/col?
body: <p>I have multiple tables like this saved in CSVs.</p>
  
  <pre><code>Table 1: Columns A,B
  Table 2: Columns A,C
  Table 3: Columns A,D
  Table 4: Columns A,E
  Table 5: Columns A,F
  Table 6: Columns A,G
  </code></pre>
  
  <p>All values are floating point, except for Column A. Column A is not set as an index, though using pandas I have that option. All entries for Column A are the same throughout all the tables.</p>
  
  <p>I want to create a table with columns A,B,C,D,E,F,G for the purpose of computing a weighted sum of columns B-G.  I have two general things I'm thinking:</p>
  
  <ol>
  <li><p>What is the best way to create a pandas dataframe with these columns? By 'best', I mean keep the ram low, and hopefully utilize some kind of parallel computing.</p></li>
  <li><p>I want to persist this dataframe on disk, so I am thinking maybe there is a better way using command line tools like sed/awk/cut to get a csv going which I can then just load.  Any tips there?</p></li>
  </ol>