How to fill an nd array with values from a 1d-array?

The following is a real-world problem in numPy reduced to the essentials, just with smaller dimensions.

Let's say I want to create an n-dimensional array all with dimensions (10, 10, 100):

all = np.empty((10, 10, 100))

I also have a 1d array data, simulated here as

data = np.arange(0, 100) 

for all i, j I now want to achieve that

all[i,j]=data

So I do:

all[:, :]=data

Of course that works.

But now I want to import data to all2 with shape (100, 10, 10). I could do that with

all2 = np.empty((100, 10, 10)) # new target to be populated
for i in range(100):
  for j in range(10):
    for k in range(10):
      all2[i, j, k]=data[i]

But is there an easier way to do this without looping? I would be surprised if it couldn't be done more elegantly, but I don't see how.

You can use transpose: all2.T[:] = data (note the second , : insn't necessary)