title: Return index values of a sorted row using pandas?
body: <p>I just recently discovered the power of pandas. (Thanks Wes McKinney!)  I have a csv that contains the following information:</p>
  
  <pre><code>RUN_START_DATE,PUSHUP_START_DATE,SITUP_START_DATE,PULLUP_START_DATE
  2013-01-24,2013-01-02,2013-01-30,2013-02-03
  2013-01-30,2013-01-21,2013-01-13,2013-01-06
  2013-01-29,2013-01-28,2013-01-01,2013-01-29
  2013-02-16,2013-02-12,2013-01-04,2013-02-11
  2013-01-06,2013-02-07,2013-02-25,2013-02-12
  2013-01-26,2013-01-28,2013-02-12,2013-01-10
  2013-01-26,2013-02-10,2013-01-12,2013-01-30
  2013-01-03,2013-01-24,2013-01-19,2013-01-02
  2013-01-22,2013-01-13,2013-02-03,2013-02-05
  2013-02-06,2013-01-16,2013-02-07,2013-01-11
  </code></pre>
  
  <p>Normally, I do not use pandas for this process.  I use the csv library to generate a lists.  Convert them using the datetime library.  I then loop through each line and run something like the following to get the sorted index of each row:</p>
  
  <pre><code>'"' + ','.join(map(str, sorted(range(len(dates)), key=lambda k: dates[k]))) + '"'
  </code></pre>
  
  <p>It then returns something like this for each line:</p>
  
  <pre><code>Out[40]: '"1,0,2,3"'
  </code></pre>
  
  <p>I then I add it at the end of each line as a new field in my csv.</p>
  
  <p>I can read the csv into pandas and convert the items to the date dtype.  I am just unsure how to go about getting the sorted index values using pandas and then flattening them into a string and putting them into a column?  Any help most appreciated!</p>