title: Forced conversion of non-numeric numpy arrays with NAN replacement
body: <p>Consider the array</p>
  
  <p><code>x = np.array(['1', '2', 'a'])</code></p>
  
  <p>Tying to convert to a float array raises an exception</p>
  
  <pre><code>x.astype(np.float)
  ValueError: could not convert string to float: a
  </code></pre>
  
  <p>Does numpy provide any efficient way to coerce this into a numeric array, replacing non-numeric values with something like NAN?</p>
  
  <p>Alternatively, is there an efficient numpy function equivalent to <code>np.isnan</code>, but which also tests for non-numeric elements like letters?</p>