[FIXED] I want to convert a 2D numpy array to a 3D array, but there's a catch

Issue

I'll use a simple 2D array with shape (4,4) as an example:

array([[0, 2, 6, 3],
   [3, 7, 3, 9],
   [0, 8, 3, 4],
   [4, 6, 2, 1]])

And to visualize it:

I want to convert this to a 3D array, so that the values a duplicated along the z-axis, as such:

So that the resulting array has a shape (4,4,3)

It seems really simple, but I can't seem to think of any way to do this.

Edit: I tried np.tile from the answers below, however I would like the output to be this:

array([[[0, 0, 0],
    [2, 2, 2],
    [6, 6, 6],
    [3, 3, 3]],

   [[3, 3, 3],
    [7, 7, 7],
    [3, 3, 3],
    [9, 9, 9]],

   [[0, 0, 0],
    [8, 8, 8],
    [3, 3, 3],
    [4, 4, 4]],

   [[4, 4, 4],
    [6, 6, 6],
    [2, 2, 2],
    [1, 1, 1]]])

I tried changing which axis is duplicated and reshaping, although it doesn't work.

Solution

You can use numpy.tile for this

>>> import numpy as np
>>> data = np.array([[0, 2, 6, 3],
                     [3, 7, 3, 9],
                     [0, 8, 3, 4],
                     [4, 6, 2, 1]])
>>> np.tile(data, (3,1,1))
array([[[0, 2, 6, 3],
        [3, 7, 3, 9],
        [0, 8, 3, 4],
        [4, 6, 2, 1]],

       [[0, 2, 6, 3],
        [3, 7, 3, 9],
        [0, 8, 3, 4],
        [4, 6, 2, 1]],

       [[0, 2, 6, 3],
        [3, 7, 3, 9],
        [0, 8, 3, 4],
        [4, 6, 2, 1]]])

Answered By - Cory Kramer