title: converters for python pandas
body: <p>I have a .txt data where columns 6 and 7 are GPS position in the form:</p>
  
  <pre><code>50;18.5701400N,4;07.7693770E
  </code></pre>
  
  <p>When I read it by read_csv I try to convert it to cartesian coordinates by using converters. I wrote the function for converter</p>
  
  <pre><code>convertFunc = lambda x : float((x[0:5]+x[6:12]).replace(';','.'))
  convert = {6:convertFunc,7:convertFunc}
  </code></pre>
  
  <p>when I use it on single value it works how I would like:</p>
  
  <pre><code>convertFunc(myData.Lat[1])
  Out [159]:  55.187110250000003
  </code></pre>
  
  <p>when I try to use it in read_csv it does not work</p>
  
  <pre><code>myData = DataFrame(read_csv('~/data.txt', sep=',' names=['A', 'B', 'C', 'D', 'E', 'Lat', 'Long'],converters=convert))
  </code></pre>
  
  <p>I have an error:</p>
  
  <pre><code>...
  convertFunc = lambda x : float((x[0:5] + x[6:12]).replace(';', '.'))
  ValueError: invalid literal for float(): DGPS ongitu
  </code></pre>
  
  <p>I don't know where do it wrong or what I misunderstand in converters?
  Or maybe anyone knows good way (package) to work with GPS data in that form?</p>
  
  <p>(I think it can be some problem with <code>lambda</code> When I want to apply my function to the column  I have an error: <code>TypeError: only length-1 arrays can be converted to Python scalars</code>)</p>