title: How to ignore junk data while extracting data from text file to pandas?
body: <p>I have <a href="https://fred.stlouisfed.org/data/PERMIT.txt" rel="nofollow noreferrer">url</a> which contains a text file which I want to load into pandas dataframe. But there is some metadata at the top which I am not able to skip while parsing and it returns error.</p>
  
  <pre><code>ParserError: Error tokenizing data. C error: Expected 1 fields in line 3, saw 2
  </code></pre>
  
  <p>This is the code I have:</p>
  
  <pre><code>import pandas as pd
  data = pd.read_csv('https://fred.stlouisfed.org/data/PERMIT.txt')
  </code></pre>
  
  <p>This code usually works for me when there is no metadata at the top. How do I skip the meta data while loading?</p>
  
  <p>The beginning of the <code>txt</code> file looks like:</p>
  
  <pre><code>Title:               New Private Housing Units Authorized by Building Permits
  Series ID:           PERMIT
  Source:              U.S. Bureau of the Census, U.S. Department of Housing and Urban Development
  Release:             New Residential Construction
  Seasonal Adjustment: Seasonally Adjusted Annual Rate
  Frequency:           Monthly
  Units:               Thousands of Units
  Date Range:          1960-01-01 to 2018-03-01
  Last Updated:        2018-04-24 7:01 AM CDT
  Notes:               Starting with the 2005-02-16 release, the series reflects an increase
                       in the universe of permit-issuing places from 19,000 to 20,000 places.
  
  DATE        VALUE
  1960-01-01   1092
  1960-02-01   1088
  1960-03-01    955
  1960-04-01   1016
  1960-05-01   1052
  1960-06-01    958
  1960-07-01    999
  1960-08-01    994
  </code></pre>