title: Convert a numpy array to a CSV string and a CSV string back to a numpy array
body: <p>I have to convert a numpy array of floats to a string (to store in a SQL DB) and then also convert the same string back into a numpy float array.</p>
  
  <p>This is how I'm going to a string (<a href="http://www.skymind.com/~ocrow/python_string/" rel="noreferrer">based on this article</a>)</p>
  
  <pre><code>VIstring = ''.join(['%.5f,' % num for num in VI])
  VIstring= VIstring[:-1] #Get rid of the last comma
  </code></pre>
  
  <p>So firstly this does work, is it a good way to go? Is their a better way to get rid of that last comma? Or can I get the <code>join</code> method to insert the commas for me?</p>
  
  <p>Then secondly,more importantly, is there a clever way to get from the string back to a float array?</p>
  
  <p>Here is an example of the array and the string:</p>
  
  <pre><code>VI
  array([ 17.95024446,  17.51670904,  17.08894626,  16.66695611,
          16.25073861,  15.84029374,  15.4356215 ,  15.0367219 ,
          14.64359494,  14.25624062,  13.87465893,  13.49884988,
          13.12881346,  12.76454968,  12.40605854,  12.00293814,
          11.96379322,  11.96272486,  11.96142533,  11.96010489,
          11.95881595,  12.26924591,  12.67548634,  13.08158864,
          13.4877041 ,  13.87701221,  14.40238245,  14.94943786,
          15.49364166,  16.03681428,  16.5498035 ,  16.78362298,
          16.90331119,  17.02299387,  17.12193689,  17.09448654,
          17.00066063,  16.9300633 ,  16.97229868,  17.2169709 ,  17.75368411])
  
  VIstring
  '17.95024,17.51671,17.08895,16.66696,16.25074,15.84029,15.43562,15.03672,14.64359,14.25624,13.87466,13.49885,13.12881,12.76455,12.40606,12.00294,11.96379,11.96272,11.96143,11.96010,11.95882,12.26925,12.67549,13.08159,13.48770,13.87701,14.40238,14.94944,15.49364,16.03681,16.54980,16.78362,16.90331,17.02299,17.12194,17.09449,17.00066,16.93006,16.97230,17.21697,17.75368'
  </code></pre>
  
  <p>Oh yes and the loss of precision from the <code>%.5f</code> is totally fine, these values are interpolated by the original points only have 4 decimal place precision so I don't need to beat that. So when recovering the numpy array, I'm happy to only get 5 decimal place precision (obviously I suppose)</p>