title: Pandas read_table with sep = '::'
body: <p>I'm going through <em>Python for Data Analysis</em> and in Chapter 2 there are introductory examples I'm working through.  On page 27 it shows the following code:</p>
  
  <pre><code>import pandas as pd
  users = pd.read_table('ml-1m/users.dat', sep='::', header=None,
  names=unames)
  </code></pre>
  
  <p>Here's a link to the github .dat file:
  <a href="https://github.com/wesm/pydata-book/tree/2nd-edition/datasets/movielens" rel="nofollow noreferrer">https://github.com/wesm/pydata-book/tree/2nd-edition/datasets/movielens</a></p>
  
  <p>When this code is run I get the following error:</p>
  
  <pre><code>(base) C:\Users\d.kelly\Desktop\Python\PforDA&gt;pforda.py
  C:\Users\d.kelly\Desktop\Python\PforDA\PforDA.py:3: ParserWarning: Falling back
  to the 'python' engine because the 'c' engine does not support regex separators
  (separators &gt; 1 char and different from '\s+' are interpreted as regex); you can
   avoid this warning by specifying engine='python'.
    users = pd.read_table('users.dat', sep = '::', header = None, names = unames)
  </code></pre>
  
  <p>I'm using Anaconda and Python 3 - pretty sure the book was written for Python 2.7, but I would still like to know how to get this example to work without the error messages. Wes is a smart guy and I'm sure having 2 digit separators is something I'll encounter again.</p>
  
  <p>My question is, in Python 3 what is the right way to use Pandas's read_table to read 2 digit separators and not get warnings?</p>