title: Python 2D numpy array from genfromtxt
body: <p>I have data files with mixed string and numerical content. I.e.:</p>
  
  <pre><code>tag1 0.1 0.2 0.3
  tag2 0.2 0.3 0.5
  tag3 0.1 0.4 0.5
  tag2 0.4 0.3 0.2
  tag1 0.3 0.3 0.1
  tag3 0.2 0.1 0.4
  </code></pre>
  
  <p>The ultimate goal is to extract an array to analyze (maybe plot) from column 2 and 3 for all elements where the tag is 'tag2'. (and other permutations thereof)</p>
  
  <p>There was another discussion on stackoverflow indicating that reading the files would be best done by <code>genfromtxt</code> use <code>dtype=None</code> to understand the ascii entries.</p>
  
  <p>Following that idea I tried;</p>
  
  <pre><code>x= np.genfromtxt('data1.rpt',dtype=None)
  </code></pre>
  
  <p>I expected a 2D array with 6 rows and 4 columns. But it turns out I got an array with 6 rows and some unexpected composite entries.</p>
  
  <pre><code>&gt;&gt;&gt; x= np.genfromtxt('data1.rpt',dtype=None)
  &gt;&gt;&gt; x
  array([('tag1', 0.1, 0.2, 0.3), ('tag2', 0.2, 0.3, 0.5),
         ('tag3', 0.1, 0.4, 0.5), ('tag2', 0.4, 0.3, 0.2),
         ('tag1', 0.3, 0.3, 0.1), ('tag3', 0.2, 0.1, 0.4)], 
        dtype=[('f0', 'S4'), ('f1', '&lt;f8'), ('f2', '&lt;f8'), ('f3', '&lt;f8')])
  &gt;&gt;&gt; x.shape
  (6,)
  &gt;&gt;&gt; 
  </code></pre>
  
  <p>What is the best way to process the files into an array which then can be filtered or sliced for content?</p>
  
  <p>Your feedback is appreciated.</p>