title: pandas shifts column names and fills last column with NAN
body: <p>I have a csv file that is tab delimited. </p>
  
  <pre><code>Example:
  Rec#    Cyc#    Step    Test (Sec)  Step (Sec)  Amp-hr  Watt-hr Amps    Volts   State   ES  DPt Time
  1   0   1   0.00000000  0.00000000  0.00000000  0.00000000  0.00000000  3.41214609  R   0   09:44:13    
  2   0   1   30.00000000 30.00000000 0.00000000  0.00000000  0.00000000  3.41077280  R   1   09:44:43    
  3   0   1   60.00000000 60.00000000 0.00000000  0.00000000  0.00000000  3.41077280  R   1   09:45:13
  </code></pre>
  
  <p>I read the csv in using:</p>
  
  <pre><code>import pandas as pd
  
  df = pd.read_csv('foo.csv', sep='\t')
  </code></pre>
  
  <p>This gives the output:</p>
  
  <pre><code>    Rec#  Cyc#     Step  Test (Sec)  Step (Sec)    Amp-hr   Watt-hr      Amps  Volts  State      ES  DPt Time
  1      0     1     0.00        0.00    0.000000  0.000000  0.000000  3.412146   R      0  09:44:13       NaN
  2      0     1    30.00       30.00    0.000000  0.000000  0.000000  3.410773   R      1  09:44:43       NaN
  3      0     1    60.00       60.00    0.000000  0.000000  0.000000  3.410773   R      1  09:45:13       NaN
  </code></pre>
  
  <p>This seems to have shifted my column names over by one and causes my last column to be filled with NAN's instead of dates.  </p>
  
  <p>If I do the following:</p>
  
  <pre><code>import pandas as pd
  
  df = pd.read_csv("foo.csv", sep="\t")
  df = pd.read_csv("foo.csv", sep="\t", usecols=df[:len(df.columns)])
  </code></pre>
  
  <p>I get the following output:</p>
  
  <pre><code>    Rec#  Cyc#   Step  Test (Sec)  Step (Sec) Amp-hr   Watt-hr      Amps  Volts  State    ES  DPt Time
  1   1      0     1     0.00        0.00    0.000000  0.000000  0.000000  3.412146   R      0  09:44:13
  2   2      0     1    30.00       30.00    0.000000  0.000000  0.000000  3.410773   R      1  09:44:43
  3   3      0     1    60.00       60.00    0.000000  0.000000  0.000000  3.410773   R      1  09:45:13      
  </code></pre>
  
  <p>Also if I try to just grab two specific columns it seems to grab those correctly.  As in df = df = pd.read_csv("foo.csv", sep="\t", usecols=[3, 8]) will correctly grab the Time (Sec) column and the Volts Column.</p>
  
  <p>I was hoping there was a way to correctly frame the data that wouldn't require me reading it twice.</p>
  
  <p>Thanks in advance!</p>
  
  <p>Oniwa</p>