NumPy vstack()

In this tutorial, you will learn about the numpy.vstack() method with the help of examples.

The vstack() method stacks the given sequence of input arrays vertically.

Example

import numpy as np

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

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

print(stackedArray)

'''
Output

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

vstack() Syntax

The syntax of vstack() is:

numpy.vstack(tup)

vstack() Arguments

The vstack() method takes a single argument:

tup - a tuple of arrays to be stacked

Note: The shape of all arrays in a given tuple must be the same, except the first dimension because we are stacking in axis 0.

vstack() Return Value

The vstack() method returns the vertically stacked array.

Example 1: Vertically Stack Arrays

import numpy as np

array1 = np.array([[0, 1], [2, 3]])
array2 = np.array([[4, 5], [6, 7]])
array3 = np.array([[8, 9]])

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

print(stackedArray)

Output

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

Example 2: Vertically Stack Arrays of Invalid Shapes

import numpy as np

array1 = np.array([[0, 1], [2, 3]])
array2 = np.array([[4, 5, 6], [7, 8, 9]])

# stacks the arrays 
stackedArray = np.vstack((array1, array2))

print(stackedArray)

Output

ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 2 and the array at index 1 has size 3