NumPy hstack()

import numpy as np

array1 = np.array([[0, 1], [2, 3]])
array2 = np.array([[4, 5], [6, 7]])

# stack the arrays 
stackedArray = np.hstack((array1, array2))

print(stackedArray)

'''
Output

[[0 1 4 5]
 [2 3 6 7]]
'''

hstack() Syntax

The syntax of hstack() is:

numpy.hstack(tup)

hstack() Argument

The hstack() method takes a single argument:

• tup - a tuple of arrays to be stacked

hstack() Return Value

The hstack() method returns the horizontally stacked array.

Example 1: Horizontally Stack 3 Arrays

import numpy as np

# arrays with shape (2,2)
array1 = np.array([[0, 1], [2, 3]])
array2 = np.array([[4, 5], [6, 7]])

# array with shape (2, 1)
array3 = np.array([[8], [9]])

# stack the arrays 
stackedArray = np.hstack((array1, array2, array3))

print(stackedArray)

Output

[[0 1 4 5 8]
 [2 3 6 7 9]]

Here, we have stacked 3 arrays of different shapes.

The shape of array3 is (2,1), yet we could stack it with arrays of shape (2, 2) because only the second dimension (2, 1) of array3 is different from the other 2 arrays.

Example 2: Horizontally Stack Arrays With Invalid Shapes

import numpy as np

# arrays with shape (2, 2)
array1 = np.array([[0, 1], [2, 3]])
array2 = np.array([[4, 5], [6, 7]])

# arrays with shape (1, 2)
array3 = np.array([[8, 9]])

# stack the arrays with invalid shape 
stackedArray = np.hstack((array1, array2, array3))

print(stackedArray)

Output

ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 0, the array at index 0 has size 2 and the array at index 2 has size 1

Here, the shape of array3 is (1, 2), which conflicts while stacking with arrays of shape (2,2).