import numpy,urllib
import matplotlib.pyplot as plt

amo = numpy.genfromtxt(urllib.urlopen("http://www.esrl.noaa.gov/psd/data/correlation/amon.us.long.data"), skip_header=1, skip_footer=4)

#print amo
data = amo[:,1:].flatten()
date = numpy.arange( amo[0,0]+1/24., amo[-1,0]+1, 1/12. ) + 0.5
use = numpy.logical_and(date>1880,date<2011)
date = date[use]
data = data[use]
date.shape = [131,12]
data.shape = [131,12]
years  = numpy.mean(date,axis=1)
annual = numpy.mean(data,axis=1)

plt.plot( years, annual )
plt.show()

for i in range(131):
  print "%4d %8.4f"%(int(years[i]),annual[i])