[FIXED] Cell wise concatenation of python arrays

Issue

I have multiple arrays of equal size, and I want to concatenate the values in each cell to produce an output array of the same size, but where each element is a list. How can I do this?

Example.

Input:
a = [[1,2],
     [3,4]]
b = [[5,6],
     [7,8]]

Desired output:
c = [[[1,5],[2,6]],
     [[3,7],[4,8]]]

How can I achieve this? My arrays are actually NumPy arrays, if that helps.

Followup Question: Concatenate Iteratively

The first answer suggests using np.dstack, which works for the above example.

How do I do the concatenation in an iterative fashion? After obtaining

c = [[[1,5],[2,6]],
     [[3,7],[4,8]]]

if I have

d = [[9,10],
     [11,12]]

I want to "concatenate" c and d to obtain

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

Solution

You can use np.dstack.

>>> a
array([[1, 2],
       [3, 4]])
>>> b
array([[5, 6],
       [7, 8]])
>>> np.dstack((a,b))
array([[[1, 5],
        [2, 6]],

       [[3, 7],
        [4, 8]]])

See help(np.dstack) for more information and examples

>>> help(np.dstack)
Help on function dstack in module numpy:

dstack(tup)
    Stack arrays in sequence depth wise (along third axis).

    This is equivalent to concatenation along the third axis after 2-D arrays
    of shape `(M,N)` have been reshaped to `(M,N,1)` and 1-D arrays of shape
    `(N,)` have been reshaped to `(1,N,1)`. Rebuilds arrays divided by
    `dsplit`.

    This function makes most sense for arrays with up to 3 dimensions. For
    instance, for pixel-data with a height (first axis), width (second axis),
    and r/g/b channels (third axis). The functions `concatenate`, `stack` and
    `block` provide more general stacking and concatenation operations.

    Parameters
    ----------
    tup : sequence of arrays
        The arrays must have the same shape along all but the third axis.
        1-D or 2-D arrays must have the same shape.

    Returns
    -------
    stacked : ndarray
        The array formed by stacking the given arrays, will be at least 3-D.

    Examples
    --------
    >>> a = np.array((1,2,3))
    >>> b = np.array((2,3,4))
    >>> np.dstack((a,b))
    array([[[1, 2],
            [2, 3],
            [3, 4]]])

    >>> a = np.array([[1],[2],[3]])
    >>> b = np.array([[2],[3],[4]])
    >>> np.dstack((a,b))
    array([[[1, 2]],
           [[2, 3]],
           [[3, 4]]])

Answered By - Abdul Niyas P M