numpy.dstack() function with example in python | 2019
numpy.dstack(): This function 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.
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.
stacked : ndarray
The array formed by stacking the given arrays, will be at least 3-D.
import numpy as np x=np.array([1,2,3,4,5]) y= np.array([6,7,8,9,10]) z=np.dstack((x, y)) print(z)