Analysis of nobel prize winners and their ages

gistfile1.py

from bs4 import BeautifulSoup
import unicodedata
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from scipy.stats import norm

class Prize:
  def __init__(self, name, age, year, prize_type, description):
    self.name = unicodedata.normalize('NFKD', name).encode('ascii','ignore') #umlaut issues
    self.age = age
    self.year = year
    self.prize_type = prize_type
    self.description = description

  def __str__(self):
    return self.name + ' won ' + str(self.prize_type) + ' at age ' + str(self.age) + ' in ' + str(self.year)

f = open('nobel_laureates_by_age.html', 'r')
html = BeautifulSoup(f.read())

winners = []
prize_types = set()
nobel_prize_string = "The Nobel Prize in "
for tag in html.find("div", id="nobel-age-info").children:
  # we're looking for a specific div, that doesn't have a class, id, or anything noteworthy
  #so I'm going to count the divs that are in this outerdiv until we hit the one I want
  if tag.name == None:
    next
  elif tag.name == 'h3':
    current_age = int(tag.text.split(" ")[-1]) #update the age
  elif tag.name == 'div':
    name = tag.find("h6").text #winner's name
    description = tag.find_all("p")[0].find("a").text #winner's name
    year = int(description.split(' ')[-1])
    prize_type = ' '.join(description.split(' ')[0:-1])
    prize_types.add(prize_type)
    prize = Prize(name, current_age, int(year), prize_type)
    winners.append(prize)

all_prize_string = "All Prizes"
ts = list(prize_types)
ts.append(all_prize_string) #want to get all prizes too

print "Type, Number of Winners, Mean Age, Variance of Ages"
for prize_type in ts:
  ages = [p.age for p in winners if p.prize_type == prize_type or prize_type == all_prize_string]
  num_bins = ages[-1] - ages[0]
  fig = plt.figure()
  n, bins, patches = plt.hist(ages, num_bins, normed=1, facecolor='green', alpha=0.2)
  mean, var = norm.fit(ages)
  y = mlab.normpdf(bins, mean, var)
  plt.plot(bins, y, 'r--')
  plt.ylabel('Number of Winners')
  plt.xlabel('Age')
  plt.title(prize_type + '. Mean: ' + str(round(mean,2)) + ', Var: ' + str(round(var,2)))
  fig.savefig('nobel_hist_' + prize_type.lower().replace(' ', '_') + '.png', dpi=500,format='png')
  print prize_type +', '+ str(len(ages)) +', '+ str(round(mean,2)) +', '+ str(round(var,2))