On Mon, Mar 8, 2010 at 2:34 PM, dimitri pater - serpia
<dimitri.pa...@gmail.com> wrote:
> Hi,
>
> I have two related lists:
> x = [1 ,2, 8, 5, 0, 7]
> y = ['a', 'a', 'b', 'c', 'c', 'c' ]
>
> what I need is a list representing the mean value of 'a', 'b' and 'c'
> while maintaining the number of items (len):
> w = [1.5, 1.5, 8, 4, 4, 4]
>
> I have looked at iter(tools) and next(), but that did not help me. I'm
> a bit stuck here, so your help is appreciated!
from __future__ import division
def group(keys, values):
#requires None not in keys
groups = []
cur_key = None
cur_vals = None
for key, val in zip(keys, values):
if key != cur_key:
if cur_key is not None:
groups.append((cur_key, cur_vals))
cur_vals = [val]
cur_key = key
else:
cur_vals.append(val)
groups.append((cur_key, cur_vals))
return groups
def average(lst):
return sum(lst) / len(lst)
def process(x, y):
result = []
for key, vals in group(y, x):
avg = average(vals)
for i in xrange(len(vals)):
result.append(avg)
return result
x = [1 ,2, 8, 5, 0, 7]
y = ['a', 'a', 'b', 'c', 'c', 'c' ]
print process(x, y)
#=> [1.5, 1.5, 8.0, 4.0, 4.0, 4.0]
It could be tweaked to use itertools.groupby(), but it would probably
be less efficient/clear.
Cheers,
Chris
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