[Python] Pandas ValueError : Must have equal len keys and value when setting with an iterable

I have a question regarding a transformation I want to add to a Dataframe pandas. I have a dataframe df with the following columns :

df.columns = Index(['S', 'HZ', 'Z', 'Demand'], dtype='object')

I want to perform the following transformation:

for s in range(S):
for t in range(HZ):
for z in range(Z):
df.loc[(df['S'] == s) & (df['HZ'] == t) & (df['Z'] == z), 'Demand'] = D[t][z]


Where D is a numpy array with the corresponding dimensions. Here is a simple example of what I try to do (with T = 0 for making it simpler).

Here is df before :

S HZ Z Demand
0 0 0 0 0
1 0 0 1 0
2 0 1 0 0
3 0 1 1 0
4 0 2 0 0
5 0 2 1 0
6 1 0 0 0
7 1 0 1 0
8 1 1 0 0
9 1 1 1 0
10 1 2 0 0
11 1 2 1 0


Here is D :

D = [[[1, 2],
[3, 4],
[5, 6]],
[[7, 8],
[9, 10],
[11, 12]]]


And here is what i want:

S HZ Z Demand
0 0 0 0 1
1 0 0 1 2
2 0 1 0 3
3 0 1 1 4
4 0 2 0 5
5 0 2 1 6
6 1 0 0 7
7 1 0 1 8
8 1 1 0 9
9 1 1 1 10
10 1 2 0 11
11 1 2 1 12


This code functions, but it is very long, so I tried something else to avoid the for loops :

df.loc[df['HZ'] >= T, 'Demand'] = D[df['S']][df['HZ']][df['Z']]


Which raises the following error :

ValueError: Must have equal len keys and value when setting with an iterable


I am searching what this error means, how to fix it if possible, and if not possible, is there a mean to do what I want without using for loops ?

Thanks by advance

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