Random Drawing Simulation -- performance issue

[Brendon Towle]

I need to simulate scenarios like the following: "You have a deck of  
3 orange cards, 5 yellow cards, and 2 blue cards. You draw a card,  
replace it, and repeat N times."

So, I wrote the following code, which works, but it seems quite slow  
to me. Can anyone point out some obvious thing that I'm doing  
inefficiently? Or, is this more or less as good as it gets?

For reference, my typical numbers look like this:

   2 <= len(population) <= 7
   4 <= len(mapping) <= 50
   10 <= count <= 1000000

B.

<code>
#!/usr/bin/env python

import random

def randomDrawing(count, population):
     """Simulates drawing <count> items from <population>, with  
replacement.
     population is a list of lists: [[count1, type1], [count2,  
type2], ...]

     Typical examples:
     >>>randomDrawing(100, [[3, 'orange'], [5, 'yellow'], [2, 'blue']])
     [[28, 'orange'], [57, 'yellow'], [15, 'blue']]

     >>>randomDrawing(100000, [[3, 'orange'], [5, 'yellow'], [2,  
'blue']])
     [[29923, 'orange'], [50208, 'yellow'], [19869, 'blue']]

     """
     res = [[0, item[1]] for item in population]
     mapping = []
     for i in xrange(len(population)):
         mapping.extend([i]*population[i][0])
     for i in xrange(count):
         index = random.choice(mapping)
         res[index][0] += 1
     return res

</code>

-- 
Brendon Towle, PhD
Cognitive Scientist
+1-412-690-2442x127
Carnegie Learning, Inc.
The Cognitive Tutor Company ®
Helping over 375,000 students in 1000 school districts succeed in math.