title: reading tab-delimited data without header in pandas
body: <p>I'm having trouble using <code>pandas</code> to open tab-delimited data without headers.</p>
  
  <p>My test data (actually contains 200 lines, of which I am showing the first 10):</p>
  
  <pre><code>Tag19184    CTAAC   hffef   1   a   36  -   chr1    10006   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10012   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10018   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10024   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10030   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10036   0   36M 36
  Tag19184    CTAAC   hffef   1   a   36  -   chr1    10042   0   36M 36
  Tag20198    CTAAC   hffef   1   a   36  -   chr1    10048   0   36M 36
  Tag20198    CTAAC   hffef   1   a   36  -   chr1    10054   0   36M 36
  Tag45093    CTAAC   hffef   1   a   36  -   chr1    10060   0   36M 36
  </code></pre>
  
  <p>My code:</p>
  
  <pre><code>import pandas as pd
  df = pd.read_csv('in_test.txt',sep='\t',header=None)
  print df
  </code></pre>
  
  <p>However, I get the following output, which I don't think I can use to further process data (?):</p>
  
  <pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;
  Int64Index: 200 entries, 0 to 199
  Data columns:
  X.1     200  non-null values
  X.2     200  non-null values
  X.3     200  non-null values
  X.4     200  non-null values
  X.5     200  non-null values
  X.6     200  non-null values
  X.7     200  non-null values
  X.8     200  non-null values
  X.9     200  non-null values
  X.10    200  non-null values
  X.11    200  non-null values
  X.12    200  non-null values
  dtypes: int64(5), object(7)
  </code></pre>
  
  <p>The <a href="http://pandas.pydata.org/pandas-docs/dev/io.html">tutorial here</a> suggests that <code>print df</code> should just give me the corresponding data frame. What am I doing wrong?</p>