In the realm of data science and computational tasks, 3D Numpy arrays are a vital tool for managing multi-dimensional data. This thread explores the different techniques of initializing these arrays with random values, along with example codes. 1. Using the np.empty function: 2. Using the np.zeros ... More on discuss.datasciencedojo.com

In Python when using np.empty(), ... an array that is really empty/have no values but have given dimensions/shape? ... I think OP is looking for a variable that has shape but doesn't really have values. ... Yes, what @Sraw said is what I mean by empty. ... A numpy array always ... More on stackoverflow.com

I can't say I fully followed your problem statement, but you can create an array with a total size of zero if any of the dimensions has size zero: a = np.empty((0, 3)) # Doesn't really matter if you use `empty`, `zeros` or `ones` here Zero-size arrays are the neutral element wrt. concatenation along their zero-size dimension (if that's what you mean by "merging"): b = np.random.uniform(size=(20, 3)) c = np.concatenate([a, b], 0) (c == b).all() # True More on reddit.com

First of all, you wouldn't get confused with your bracketing if you wrote it a little differently: int map[2][3][5] = { { {0,0,0,0,0}, {0,0,0,0,0}, {0,0,0,0,0} }, { {0,0,0,0,0}, {0,0,0,0,0}, {0,0,0,0,0} } } Anyway, you basically have two options: Option 1: list of lists of lists x, y, z = 2, 3, 5 map = [] for _ in range(x): sublist = [] for _ in range(y): subsublist = [0] * z sublist.append(subsublist) map.append(sublist) This can be written more compactly using nested list comprehensions: x, y, z = 2, 3, 5 map = [[[0 for c in range(z)] for b in range(y)] for a in range(x)] Doing it this way, your dimensions are fixed size (you'll get IndexError if you try to access invalid indices), but it is non-ideal because it is really a list of lists of lists. You'll have to be careful not to accidentally make multiple references to the same sublists, because that would probably lead to confusing unexpected results. Option 2: dictionary with (x, y, z) tuples as the keys x, y, z = 2, 3, 5 map = {(a, b, c): 0 for a in range(x) for b in range(y) for c in range(z)} # Now access items like map[(2, 3, 5)] # or even map[2, 3, 5] This is nice because the set-up is simpler. The downside is that there's no safeguard against adding new items with out-of-bounds indices. EDIT: Probably a good idea to call this something other than map, because map() is a built-in function that you may find yourself needing to use. More on reddit.com