title: Removing NAN's from numpy 2-D arrays
body: <p>Similar to <a href="https://stackoverflow.com/questions/11453141/how-to-remove-all-rows-in-a-numpy-ndarray-that-contain-non-numeric-values">this question</a> I would like to remove some NAN's from a 2-D numpy array.  However, instead of removing an entire row that has NAN's I want to remove the corresponding element from each row of the array.  For example (using list format for simplicity)</p>
  
  <pre><code>x=[ [1,2,3,4],
      [2,4,nan,8],
      [3,6,9,0] ]
  </code></pre>
  
  <p>would become</p>
  
  <pre><code>x=[ [1,2,4],
      [2,4,8],
      [3,6,0] ]
  </code></pre>
  
  <p>I can imagine using a <code>numpy.where</code> to figure out where in each row the NAN's appear and then use some loops and logic statements to make a new array from the old array (skipping over the NAN's and the corresponding elements in the other rows) but that to me doesn't seem to be a very streamlined way to do things.  Any other ideas?</p>