title: turning a two dimensional array into a two column dataframe pandas
body: <p>if I have the following, how do I make pd.DataFrame() turn this array into a dataframe with two columns. What's the most efficient way? My current approach involves creating copies out of each into a series and making dataframes out of them. </p>
  
  <p>From this: </p>
  
  <pre><code>([[u'294 (24%) L', u'294 (26%) R'],
    [u'981 (71%) L', u'981 (82%) R'],])
  </code></pre>
  
  <p>to </p>
  
  <pre><code>x    y
  294  294
  981  981
  </code></pre>
  
  <p>rather than </p>
  
  <pre><code>x
  [u'294 (24%) L', u'294 (26%) R']
  </code></pre>
  
  <p>my current approach. Looking for something more efficient</p>
  
  <pre><code>numL = pd.Series(numlist).map(lambda x: x[0])
      numR = pd.Series(numlist).map(lambda x: x[1])
  
      nL = pd.DataFrame(numL, columns=['left_num'])
      nR = pd.DataFrame(numR, columns=['right_num'])
  
      nLR = nL.join(nR)
  
      nLR
  </code></pre>
  
  <p>UPDATE** </p>
  
  <p>I noticed that my error simply comes down to when you pd.DataFrame() a list versus a series. WHen you create a dataframe out of a list, it merges the items into the same column. Not so with a list. That solved my problem in the most efficient way. </p>