Modify passed, nested dict/list
- by Gerenuk
I was thinking of writing a function to normalize some data. A simple approach is
def normalize(l, aggregate=sum, norm_by=operator.truediv):
aggregated=aggregate(l)
for i in range(len(l)):
l[i]=norm_by(l[i], aggregated)
l=[1,2,3,4]
normalize(l)
l -> [0.1, 0.2, 0.3, 0.4]
However for nested lists and dicts where I want to normalize over an inner index this doesnt work. I mean I'd like to get
l=[[1,100],[2,100],[3,100],[4,100]]
normalize(l, ?? )
l -> [[0.1,100],[0.2,100],[0.3,100],[0.4,100]]
Any ideas how I could implement such a normalize function?
Maybe it would be crazy cool to write
normalize(l[...][0])
Is it possible to make this work?? Or any other ideas?
Also not only lists but also dict could be nested. Hmm...
EDIT:
I just found out that numpy offers such a syntax (for lists however). Anyone know how I would implement the ellipsis trick myself?
