title: convert nan value to zero
body: <p>I have a 2D numpy array. Some of the values in this array are <code>NaN</code>. I want to perform certain operations using this array. For example consider the array:</p>
  
  <pre><code>[[   0.   43.   67.    0.   38.]
   [ 100.   86.   96.  100.   94.]
   [  76.   79.   83.   89.   56.]
   [  88.   NaN   67.   89.   81.]
   [  94.   79.   67.   89.   69.]
   [  88.   79.   58.   72.   63.]
   [  76.   79.   71.   67.   56.]
   [  71.   71.   NaN   56.  100.]]
  </code></pre>
  
  <p>I am trying to take each row, one at a time, sort it in reversed order to get max 3 values from the row and take their average. The code I tried is:</p>
  
  <pre><code># nparr is a 2D numpy array
  for entry in nparr:
      sortedentry = sorted(entry, reverse=True)
      highest_3_values = sortedentry[:3]
      avg_highest_3 = float(sum(highest_3_values)) / 3
  </code></pre>
  
  <p>This does not work for rows containing <code>NaN</code>. My question is, is there a quick way to convert all <code>NaN</code> values to zero in the 2D numpy array so that I have no problems with sorting and other things I am trying to do.</p>