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:
Concatenate two 2-D arrays along columns (axis=1
):
Concatenate two 2-D arrays along rows (default axis=0
):
Завдання
You have two arrays:
[[12, 56, 78], [35, 1, 5]]
;[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array:
Все було зрозуміло?
Зміст курсу
NumPy in a Nutshell
1. Getting Started with NumPy
4. Important Functions
NumPy in a Nutshell
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:
Concatenate two 2-D arrays along columns (axis=1
):
Concatenate two 2-D arrays along rows (default axis=0
):
Завдання
You have two arrays:
[[12, 56, 78], [35, 1, 5]]
;[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array:
Все було зрозуміло?