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How to stack arrays in Numpy?

Posted on April 1, 2021June 2, 2022 By Luke K

Let’s learn how to stack arrays in Numpy Python library.
stack array vertically numpy vstack

Arrays are stackable. I’ll show how to stack array vertically and horizontally in Python Numpy.

Using vstack

To stack arrays vertically use Numpy vstack function.

import numpy as np

my_array = np.array([[0, 1], [2, 4], [5, 6]])
my_second_array = np.array([[1, 4], [3, 7], [5, 8]])

stacked_array = np.vstack((my_array, my_second_array))
print(f"Arrays stacked vertically: \n {stacked_array}")

stack array vertically numpy vstack

Using hstack

Similarlly you can stack array horizontally with Numpy hstack function.

import numpy as np

my_array = np.array([[0, 1], [2, 4], [5, 6]])
my_second_array = np.array([[1, 4], [3, 7], [5, 8]])

stacked_array = np.hstack((my_array, my_second_array))
print(f"Arrays stacked horizontally: \n {stacked_array}")

stack array horizontally numpy hstack

Stacking based on dimensions

There is also a possible to stack array based on dimensions configured by Numpy stack axis parameter.

See also  How to calculate standard deviation in Numpy?

Let’s see above example with two different axis parameters based on -1 and 1 dimension of stacking.

import numpy as np

my_array = np.array([[0, 1], [2, 4], [5, 6]])
my_second_array = np.array([[1, 4], [3, 7], [5, 8]])

stacked_array = np.stack((my_array, my_second_array), axis=-1)
print(f"Arrays stacked using axis=-1: \n {stacked_array}")
stacked_array = np.stack((my_array, my_second_array), axis=1)
print(f"Arrays stacked using axis=1: \n {stacked_array}")

stack array axis dimensions

As you can see there are difference in outputs depends on axis parameter chosen.
For 3-dimension axes you can set axis parameter between -3 and 3 (including 0). For every other value you will get different outputs.

See also  How to trim an array with Numpy clip?

Using dstack

The other stacking possibility is also third axis stack. There is Numpy dstack function for that.

import numpy as np

my_array = np.array([[0, 1], [2, 4], [5, 6]])
my_second_array = np.array([[1, 4], [3, 7], [5, 8]])

stacked_array = np.dstack((my_array, my_second_array))
print(f"Third axis stack: \n {stacked_array}")

numpy third array stack

Now you know so many ways to stack arrays in Python Numpy.

See also  How many distinct values in array?
numpy Tags:array, axis, dimension, stack

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