title: Pandas - read_table read selected lines
body: <p>I work with text files that contain some basic information in the first 6 rows including empty rows. I have to import, process and export the data into another csv. Here is an example of the first 6 rows:</p>
  
  <pre><code>Foov7.9 - bar.raw created at 10:45:25 on 10.02.2015:
  (empty row)
  (empty row)
  A B C D
  a b c d
  (empty row)
  </code></pre>
  
  <p>In pandas I use row 4:</p>
  
  <pre><code>A B C D
  </code></pre>
  
  <p>as header for the dataframe:</p>
  
  <pre><code>data1 = pd.read_table(dataset1,header = 1, skiprows = (4,5), index_col=None, delimiter=r"\t", engine='python')
  </code></pre>
  
  <p>When writing to_csv after processing the data I now would like to place back the first 6 rows but I already fail when reading the rows. By solely writing the header from row 4 into the csv I would loose all additional information.
  How can I read these rows and later put them back into the csv without interfering with the dataframe header?</p>