Joining
Another equally important operation in array manipulation is joining arrays. Joining arrays involves combining multiple arrays into a single array that includes all the elements from each of the original arrays.
We perform this concatenation along the specified axes:
if
axis = 0(which is the default value), this implies concatenating the arrays by rows;if
axis = 1, this means concatenating the arrays by columns.
Join two arrays:
import numpy as np array_1 = np.array([54, 6, 23, 1, 6]) array_2 = np.array([12, 67, 94, 2, 8 ]) array = np.concatenate((array_1, array_2)) print(array)
Concatenate two 2-D arrays along columns (axis=1):
import numpy as np array_1 = np.array([[0, 1, 2], [3, 4, 5]]) array_2 = np.array([[6, 7, 8], [9, 10, 11]]) array = np.concatenate((array_1, array_2), axis=1) print(array)
Concatenate two 2-D arrays along rows (default axis=0):
import numpy as np array_1 = np.array([[0, 1, 2], [3, 4, 5]]) array_2 = np.array([[6, 7, 8], [9, 10, 11]]) array = np.concatenate((array_1, array_2)) print(array)
Task
Swipe to start coding
You have two arrays:
-
[[12, 56, 78], [35, 1, 5]]; -
[[ 8, 65, 3], [ 1, 2, 3]].
You have to create the following combined array:
Solution
Switch to desktop for real-world practiceContinue from where you are using one of the options belowEverything was clear?
Thanks for your feedback!
