title: Pandas: CSV header and data row size mismatch
body: <p>Is it possible to instruct Pandas to ignore columns which positions are exceeding header size?</p>
  
  <pre><code>import pandas
  
  with open('test.csv', mode='w') as csv_file:
      csv_file.write("datetime,A\n")
      csv_file.write("2018-10-09 18:00:07, 123\n")
  
  df = pandas.read_csv('test.csv')
  print(df)
  </code></pre>
  
  <p>gives the answer:</p>
  
  <pre><code>              datetime    A
  0  2018-10-09 18:00:07  123
  </code></pre>
  
  <p>However loading CSV file with more data columns, that defined in header: </p>
  
  <pre><code>with open('test.csv', mode='w') as csv_file:
      csv_file.write("datetime,A\n")
      csv_file.write("2018-10-09 18:00:07, 123, ABC, XYZ\n")
  
  df = pandas.read_csv('test.csv')
  print(df)
  </code></pre>
  
  <p>returns:</p>
  
  <pre><code>                        datetime     A
  2018-10-09 18:00:07 123      ABC   XYZ
  </code></pre>
  
  <p>Pandas shifts headers to the rightmost position of data. </p>
  
  <p>I need different behavior. I'd like pandas to ignore data rows, which goes beyond the header.</p>
  
  <p><strong>Note</strong>: I can't enumerate columns, as it's a generic use case. Due to some independent from my code reason sometimes there is more data, that expected. I'd like to ignore the extra data.</p>