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NumPy in a Nutshell
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:
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)
Swipe to show code editor
You have two arrays:
-
[[12, 56, 78], [35, 1, 5]]
; -
[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array:
Obrigado pelo seu feedback!
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)
Swipe to show code editor
You have two arrays:
-
[[12, 56, 78], [35, 1, 5]]
; -
[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array:
Obrigado pelo seu feedback!
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)
Swipe to show code editor
You have two arrays:
-
[[12, 56, 78], [35, 1, 5]]
; -
[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array:
Obrigado pelo seu feedback!
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)
Swipe to show code editor
You have two arrays:
-
[[12, 56, 78], [35, 1, 5]]
; -
[[ 8, 65, 3], [ 1, 2, 3]]
.
You have to create the following combined array: