title: numpy.polyfit doesn't handle NaN values
body: <p>I have a problem with this piece of Python-code:</p>
  
  <pre><code>import matplotlib
  matplotlib.use("Agg")
  
  import numpy as np
  import pylab as pl
  
  A1=np.loadtxt('/tmp/A1.txt',delimiter=',')
  A1_extrema = [min(A1),max(A1)]
  A2=np.loadtxt('/tmp/A2.txt',delimiter=',')
  
  pl.close()
  ab = np.polyfit(A1,A2,1)
  print ab
  fit = np.poly1d(ab)
  print fit
  r2 = np.corrcoef(A1,A2)[0,1]
  print r2
  pl.plot(A1,A2,'r.', label='TMP36 vs. DS18B20', alpha=0.7)
  pl.plot(A1_extrema,fit(A1_extrema),'c-')
  pl.annotate('{0}'.format(r2) , xy=(min(A1)+0.5,fit(min(A1))), size=6, color='r' )
  
  pl.title('Sensor correlations')
  pl.xlabel("T(x) [degC]")
  pl.ylabel("T(y) [degC]")
  pl.grid(True)
  pl.legend(loc='upper left', prop={'size':8})
  pl.savefig('/tmp/C123.png')
  </code></pre>
  
  <p>A1 and A2 are arrays containing temperature readings from different sensors. I want to find a correlation between the two and show that graphically.
  However, occasionally, sensor-read-errors occur. And in such a case a NaN is inserted in one of the files instead of a temperature value. Then the <code>np.polyfit</code> refuses to fit the data and returns <code>[nan, nan]</code> as a result. All else fails after that as well.</p>
  
  <p>My question: How can I convince <code>numpy.polyfit</code> to ignore the NaN values?
  N.B.: Datasets are relatively small at the moment. I expect that they may grow to about 200k...600k elements once deployed.</p>