title: Can't read time series data into a numpy array
body: <p>I have been trying to create a time series dataset from a .csv file.</p>
  
  <p>What I can't get around is that it has 2 time indexes: respectively the transaction date and the time, stored in two separate strings.</p>
  
  <p>When trying this:</p>
  
  <pre><code>Date, Time, Open,High,Low,Close,Volume = np.loadtxt('EURUSD.txt', unpack = True,
                                  delimiter = '\t',
                                  converters = {0:time.strptime('%Y.%m.%d')})
  </code></pre>
  
  <p>I get this error:</p>
  
  <pre><code>ValueError: invalid literal for float(): 00:00
  </code></pre>
  
  <p>which makes me suspect that the problem is the second time index.</p>
  
  <p>The data looks like that:</p>
  
  <pre><code>2009.03.10  00:00   1.26185 1.26265 1.26185 1.2623  1344
  2009.03.10  00:05   1.2623  1.26255 1.26185 1.26195 1656
  2009.03.10  00:10   1.262   1.2622  1.26155 1.26175 1068
  </code></pre>
  
  <p>Where the first and the second column are the transaction date and the time, respectively. They are separated by tab.</p>
  
  <p>Should I try and combine the two into one index? If so, how? I hope I explained my problem enough, I am entirely new to python and I have been trying to fix this for days now. If you have any questions, please feel free to ask and I will edit the post.</p>