title: Reading CSV files in numpy where delimiter is ","
body: <p>I've got a CSV file with a format that looks like this:</p>
  
  <blockquote>
    <p>"FieldName1", "FieldName2", "FieldName3", "FieldName4"<br>
    "04/13/2010 14:45:07.008", "7.59484916392", "10", "6.552373"<br>
    "04/13/2010 14:45:22.010", "6.55478493312", "9", "3.5378543"<br>
    ...</p>
  </blockquote>
  
  <p>Note that there are double quote characters at the start and end of each line in the CSV file, and the <code>","</code> string is used to delimit fields within each line.  The number of fields in the CSV file can vary from file to file.</p>
  
  <p>When I try to read this into numpy via:<br>
  <code>import numpy as np</code><br>
  <code>data = np.genfromtxt(csvfile, dtype=None, delimiter=',', names=True)</code><br>
  all the data gets read in as string values, surrounded by double-quote characters.  Not unreasonable, but not much use to me as I then have to go back and convert every column to its correct type</p>
  
  <p>When I use <code>delimiter='","'</code> instead, everything works as I'd like, <strong>except</strong> for the 1st and last fields.  As the start of line and end of line characters are a single double-quote character, this isn't seen as a valid delimiter for the 1st and last fields, so they get read in as e.g. <code>"04/13/2010 14:45:07.008</code> and <code>6.552373"</code> - note the leading and trailing double-quote characters respectively.  Because of these redundant characters, numpy assumes the 1st and last fields are both String types; I don't want that to be the case</p>
  
  <p>Is there a way of instructing numpy to read in files formatted in this fashion as I'd like, without having to go back and "fix" the structure of the numpy array after the initial read?</p>