title: Read large csv file with many duplicate values, drop duplicates while reading
body: <p>I have the following pandas code snippet that reads all the values found in a specific column of my <code>.csv</code> file.</p>
  
  <pre><code>sample_names_duplicates = pd.read_csv(infile, sep="\t", 
                                        engine="c", usecols=[4],
                                        squeeze=True)
  </code></pre>
  
  <p>That particualr column of my file contains perhaps 20 values at most (sample names), so it would probably be faster if I could drop the duplicates on the fly instead of storing them and then deleting the duplicates afterwards. Is this possible to delete duplicates as they are found in some way?</p>
  
  <p>If not, is there a way to do this more quickly, without having to make the user explicitly name what the sample names in her file are? </p>