title: NumPy: How to filter matrix lines
body: <p>I'm new to numpy and having trouble trying to filter a subset of a sample.</p>
  
  <p>I've got a matrix with the shape <code>(1000, 12)</code>. That is, a thousand samples, with 12 data columns in each. I'm willing to create two matrices, one with all the outliers in the sample, and the other with all the elements which are not outliers; The resulting matrices should have this shape:</p>
  
  <pre><code>norm.shape     = (883, 12)
  outliers.shape = (117, 12)
  </code></pre>
  
  <p>To identify an outlier, I'm using this condition:</p>
  
  <pre><code>cond_out  = (dados[0:,RD_EVAL] &gt; _max_rd) | (dados[0:,DUT_EVAL] &gt; _max_dut)
  </code></pre>
  
  <p>That is, for each line in the matrix, I'm looking for the values of two columns. If one of them is above a certain threshold, then the line is considered an outlier. The point is, this condition has a shape <code>(1000,)</code>, so when I compress the original matrix, I get a <code>(117,)</code> result. How could I filter the matrix so the result would be <code>(117,12)</code>, that is, a matrix with all the lines that are outliers, but with all the data columns in each of them?</p>