If I have a list:
a=[6,3,2,5,1,4]
and a specific size likes 3, so number 1~2 will tagged 1, 3~4 tagged 2, 5~6 tagged 3, likes list b:
b=[3,2,1,3,1,2]
How can I efficient to do this? Note that list could be floating number
Sorry for unclear description, Update with more complex example:
a=[2.5,1.4,1.6,2.1,1.5,0.7]
output will be :
b=[3,1,2,3,2,1]
This is what you need :
import math
a=[6,3,2,5,1,4]
size = 3
b = list(a)
b.sort()
for i in range(len(a)) :
w = len(b)/size #1
a[i] = math.ceil((b.index(a[i]) + 1)/(w)) #2
print(a)
1: we're getting the length of each chunk
2: we're getting in which chunk the number is present in our sorted list and replacing it with the number of the chunk in the original list
You can achieve this by first ordering the list, and splitting it into chunks of the desired size:
a=[6,3,2,5,1,4]
n = 3
a_ord = sorted(a)
def split_list(alist, wanted_parts=1):
length = len(alist)
return [ alist[i*length // wanted_parts: (i+1)*length // wanted_parts]
for i in range(wanted_parts) ]
x = split_list(a_ord,n)
And then crating a dictionary using these chunks as the bins:
d = {j:x.index(i)+1 for i in x for j in i}
print(d)
>>> {1: 1, 2: 1, 3: 2, 4: 2, 5: 3, 6: 3}
And then mapping the values using the dictionary:
b = [d[key] for key in a]
print(b)
>>> [3, 2, 1, 3, 1, 2]
sample_dict = {
1:1,
2:1,
3:2,
4:2,
5:3,
6:3
}
for k in a:
out_arr.append(sample_dict[k])
print (out_arr)
