title: Searching 2D array with numpy.where with multiple conditions
body: <p>I have a 2D array of arrays defined as follows:</p>
  
  <pre><code>traces = [['x1',11026,0,0,0,0],
            ['x0',11087,0,0,0,1],
            ['x0',11088,0,0,1,3],
            ['x0',11088,0,0,0,3],
            ['x0',11088,0,1,0,1]]
  </code></pre>
  
  <p>I want to find the index of the row which matches multiple conditions of selected columns. For example I want to find the row in this array where </p>
  
  <pre><code>row[0]=='x0' &amp; row[1]==11088 &amp; row[3]==1 &amp; row[5]=1
  </code></pre>
  
  <p>Searching on this criteria should return 4.</p>
  
  <p>I attempted to use numpy.where but can't seem to make it work with multiple conditions</p>
  
  <pre><code>print np.where((traces[:,0] == 'x0') &amp; (traces[:,1] == 11088) &amp; (traces[:,3] == 1) &amp; (traces[:,5] == 1))
  </code></pre>
  
  <p>The above creates the warning </p>
  
  <pre><code>FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison   print np.where((traces[:,0] == 'x0') &amp; (traces[:,1] == 11088) &amp; (traces[:,3]
  == 1) &amp; (traces[:,5] == 1)) (array([], dtype=int32),)
  </code></pre>
  
  <p>I've attempted to use <code>numpy.logical_and</code> as well and that doesn't seem to work either, creating similar warnings.</p>
  
  <p>Any way I can do this using <code>numpy.where</code> without iterating over the whole 2D array?</p>
  
  <p>Thanks</p>