Florian Brucker wrote:
Florian Brucker wrote:
Hi everybody!
Given a dictionary, I want to create a clustered version of it,
collecting keys that have the same value:
>>> d = {'a':1, 'b':2, 'c':1, 'd':1, 'e':2, 'f':3}
>>> cluster(d)
{1:['a', 'c', 'd'], 2:['b', 'e'], 3:['f']}
That is, generate a new dict which holds for each value of the old
dict a list of the keys of the old dict that have that very value.
Another requirement is that it should also work on lists, in that case
with indices instead of keys. We may assume that all values in the
original dict/list can be used as dict keys.
[...]
> Wow, thanks everybody! There's a lot to learn for me from these
examples...
>
>
d = {'a':1, 'b':2, 'c':1, 'd':1, 'e':2, 'f':3}
from itertools import groupby
d2 = dict(
(key, [G[1] for G in g]) for (key, g) in
groupby(
sorted( (val, key) for (key, val) in d.iteritems() ),
lambda X: X[0]
)
)
print d2
{1: ['a', 'c', 'd'], 2: ['b', 'e'], 3: ['f']}
;-) *ducks*
G.
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