title: Pandas DataFrame - desired index has duplicate values
body: <p>This is my first time trying Pandas.  I think I have a reasonable use case, but I am stumbling. I want to load a tab delimited file into a Pandas Dataframe, then group it by Symbol and plot it with the x.axis indexed by the TimeStamp column.  Here is a subset of the data:</p>
  
  <pre><code>Symbol,Price,M1,M2,Volume,TimeStamp
  TBET,2.19,3,8.05,1124179,9:59:14 AM
  FUEL,3.949,9,1.15,109674,9:59:11 AM
  SUNH,4.37,6,0.09,24394,9:59:09 AM
  FUEL,3.9099,8,1.11,105265,9:59:09 AM
  TBET,2.18,2,8.03,1121629,9:59:05 AM
  ORBC,3.4,2,0.22,10509,9:59:02 AM
  FUEL,3.8599,7,1.07,102116,9:58:47 AM
  FUEL,3.8544,6,1.05,100116,9:58:40 AM
  GBR,3.83,4,0.46,64251,9:58:24 AM
  GBR,3.8,3,0.45,63211,9:58:20 AM
  XRA,3.6167,3,0.12,42310,9:58:08 AM
  GBR,3.75,2,0.34,47521,9:57:52 AM
  MPET,1.42,3,0.26,44600,9:57:52 AM
  </code></pre>
  
  <p>Note two things about the TimeStamp column;</p>
  
  <ol>
  <li>it has duplicate values and</li>
  <li>the intervals are irregular.</li>
  </ol>
  
  <p>I thought I could do something like this...</p>
  
  <pre><code>from pandas import *
  import pylab as plt
  
  df = read_csv('data.txt',index_col=5)
  df.sort(ascending=False)
  
  df.plot()
  plt.show()
  </code></pre>
  
  <p>But the read_csv method raises an exception "Tried columns 1-X as index but found duplicates". Is there an option that will allow me to specify an index column with duplicate values?  </p>
  
  <p>I would also be interested in aligning my irregular timestamp intervals to one second resolution, I would still wish to plot multiple events for a given second, but maybe I could introduce a unique index, then align my prices to it?</p>