title: Cannot assign values to a 'double slice' using numpy
body: <p>How would I do the following in numpy?</p>
  
  <ol>
  <li>select all rows of an array containing note more than 50% 0 values.</li>
  <li>select first <code>n</code> (let's say 2) rows from all rows satisfying 1.</li>
  <li>do something and place modified rows on same index of a zero array with equal shape of 1.</li>
  </ol>
  
  <p>The following results in an array where no new values are assigned:</p>
  
  <pre><code>In [177]:    
  a = np.array([[0,0,3],[4,5,6],[7,0,0],[10,11,12],[13,14,15]])
  b = np.zeros_like(a)
  a
  Out[177]:    
  array([[ 0,  0,  3],
         [ 4,  5,  6],
         [ 7,  0,  0],
         [10, 11, 12],
         [13, 14, 15]])
  
  In [178]:
  # select all rows containg note more than 50% 0 values
  percent = np.sum(a == 0, axis=-1) / float(check.shape[1])
  percent = percent &gt;= 0.5
  slice = np.invert(percent).nonzero()[0]
  
  In [183]:
  # select first two rows satisfying 'slice'
  a[slice][0:2] 
  
  Out[183]:    
  array([[ 4,  5,  6],
         [10, 11, 12]])
  
  In [182]:
  # do something and place modified rows on same index of zero array
  b[slice][0:2] = a[slice][0:2] * 2
  
  In [184]:
  b
  Out[184]:    
  array([[0, 0, 0],
         [0, 0, 0],
         [0, 0, 0],
         [0, 0, 0],
         [0, 0, 0]])
  </code></pre>