# Read seasonal snowfalls from National Oceanic and Atmospheric Administration
import urllib

html = urllib.urlopen("http://www.erh.noaa.gov/box/climate/bossnw.shtml").read()
delim = "1891-92"
data1 = delim + html.split(delim)[1]
data2 = data1.split("\n\n")[0]

a = data2.split('\n')
b = [ (x.split()[0], x.split()[-1]) for x in a ]
c = [ (float(x[-1]), x[0]) for x in b ]
d = sorted( c, key=lambda x: x[0] )
d.reverse() # Largest snowfalls first

print( "Ten largest snowfalls:\n" +
       '\n'.join( [str((x[1], x[0])) for x in d[:10]] ) )

#=======================================
# And now graph c (snowfall in chronological order)

import matplotlib.pyplot

matplotlib.pyplot.xlabel("Year")
# The list c is: [ (46.8, '1891-92'), ... ]
# Pick out labels for [0:len(c)+1:10]  (from 0 to len(c), for every 10th elt)
matplotlib.pyplot.xticks( range(0, len(c), 10),
                          [x[1] for x in c][0:len(c)+1:10] )
locs, labels = matplotlib.pyplot.xticks()   # Get the labels field for x-axix
matplotlib.pyplot.setp(labels, rotation=45) # Rotate the labels 45 degrees
matplotlib.pyplot.axis(xmin=0)
matplotlib.pyplot.axis(xmax=len(c)+1)

matplotlib.pyplot.ylabel("Snowfall (in.)")

# This must be done after adjusting the x- and y-axes.
matplotlib.pyplot.tight_layout(w_pad=6, h_pad=6) # padding in width, height

matplotlib.pyplot.scatter(range(len(c)), [x[0] for x in c])  # scatter plot
matplotlib.pyplot.title("Seasonal snowfall in Boston")
matplotlib.pyplot.show()