Making a dictionary from two numpy arrays

Question

I have two NumPy arrays:

one named labels and the other component:

labels = array([ 0,  0,  0,  3,  0,  0,  0,  1,  0,  1,  0,  0,  2,  2,  3,  4, -1])

component = array([ 1.05325312,  1.0206622 ,  1.0372349 ,  1.06951778,  0.96379751, 0.98862576,  1.01135931,  0.92633951,  1.09095756,  1.1662432, 1.17794883,  1.23006966,  1.25465147,  1.27054648,  1.18940802, 0.91512676,  0.81926385])

I want the labels array to be the keys of the dictionary, and the elements in components to be sorted into the keys.

Both arrays are the same shape and the positions of the elements in labels correspond to the position in components.

I'm trying to get something like this:

{'-1': [0.81926385],
'0': [1.05325312, 1.0206622, 1.0372349, 0.96379751, 0.98862576, 1.01135931, 1.09095756], 
'1': [0.92633951, 1.1662432], 
'2': [1.25465147,  1.27054648], 
'3': [1.06951778, 1.18940802], 
'4': [0.91512676]}

I have tried using zip with several different methods but I can't figure out how to split the values into their associated key. Can anyone point me in the right direction?

d = dict(zip(labels, components))

maya · Accepted Answer · 2022-03-01 06:09:13Z

You can't use dict(zip(**)) directly, don't forget that the keys in the dictionary are unique, adding a judgment may solve the problem, the way I provide is to do it by a loop combined with an if statement, if the key exists then append, if not then create an empty list:

from numpy import array

labels = array([ 0,  0,  0,  3,  0,  0,  0,  1,  0,  1,  0,  0,  2,  2,  3,  4, -1])

component = array([ 1.05325312,  1.0206622 ,  1.0372349 ,  1.06951778,  0.96379751, 0.98862576,  1.01135931,  0.92633951,  1.09095756,  1.1662432, 1.17794883,  1.23006966,  1.25465147,  1.27054648,  1.18940802, 0.91512676,  0.81926385])

dic = {}
for key, value in zip(labels, component):
    if key not in dic:
        dic[key] = [value]
    else:
        dic[key].append(value)
print(dic)

If you want to be more concise, you can consider using defaultdict as well as OrderedDict

mozway · Accepted Answer · 2022-03-01 08:24:14Z

1

This is a perfect use case for collections.defaultdict:

from collections import defaultdict

d = defaultdict(list)

for l,c in zip(labels, component):
    d[l].append(c)
    
d = dict(d)

output:

{0: [1.05325312, 1.0206622, 1.0372349, 0.96379751, 0.98862576, 1.01135931, 1.09095756, 1.17794883, 1.23006966],
 3: [1.06951778, 1.18940802],
 1: [0.92633951, 1.1662432],
 2: [1.25465147, 1.27054648],
 4: [0.91512676],
-1: [0.81926385]}

answered Mar 1, 2022 at 8:24

mozway

267k13 gold badges56 silver badges106 bronze badges

Comments

lostinpython · Accepted Answer · 2022-03-01 05:41:51Z

0

Another alternative I have thought of is to use pandas.

Put both arrays into their own columns and group them by labels.

I was hoping to keep things in numpy for speed but if needs must.

pd.DataFrame(data=[X.flatten(), labels], index={'Levels', 'Zone'}).T

answered Mar 1, 2022 at 5:41

lostinpython

411 silver badge8 bronze badges

2 Comments

adir abargil Over a year ago

did you try itertools?

lostinpython Over a year ago

@adirabargil its a massive dataset, would be best to avoid for loops where possible

Collectives™ on Stack Overflow

Making a dictionary from two numpy arrays

3 Answers 3

Comments

Comments

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

Comments

Comments

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related