title: Read Values from .csv file and convert them to float arrays
body: <p>I stumbled upon a little coding problem. I have to basically read data from a .csv file which looks a lot like this:</p>
  
  <pre><code>2011-06-19 17:29:00.000,72,44,56,0.4772,0.3286,0.8497,31.3587,0.3235,0.9147,28.5751,0.3872,0.2803,0,0.2601,0.2073,0.1172,0,0.0,0,5.8922,1,0,0,0,1.2759
  </code></pre>
  
  <p>Now, I need to basically an entire file consisting of rows like this and parse them into numpy arrays. Till now, I have been able to get them into a big string type object using code similar to this:</p>
  
  <pre><code>order_hist = np.loadtxt(filename_input,delimiter=',',dtype={'names': ('Year', 'Mon', 'Day', 'Stock', 'Action', 'Amount'), 'formats': ('i4', 'i4', 'i4', 'S10', 'S10', 'i4')})
  </code></pre>
  
  <p>The format for this file consists of a set of S20 data types as of now. I need to basically extract all of the data in the big ORDER_HIST data type into a set of arrays for each column. I do not know how to save the date time column (I've kept it as String for now). I need to convert the rest to float, but the below code is giving me an error:</p>
  
  <pre><code>    temparr=float[:len(order_hist)]
      for x in range(len(order_hist['Stock'])): 
          temparr[x]=float(order_hist['Stock'][x]);
  </code></pre>
  
  <p>Can someone show me just how I can convert all the columns to the arrays that I need??? Or possibly direct me to some link to do so?</p>