NumPy Array Join

Joining NumPy Arrays

Joining refers to combining the contents of two or more arrays into a single array.

In SQL, tables are joined based on a key, while in NumPy, arrays are joined along specified axes.

To join arrays, we provide a sequence of arrays to the concatenate() function, along with the desired axis. If the axis is not explicitly specified, it defaults to 0.

Example

Join two arrays

import numpy as np

arr1 = np.array([1, 2, 3])

arr2 = np.array([4, 5, 6])

arr = np.concatenate((arr1, arr2))

print(arr)

Example

Join two 2-D arrays along the rows (axis=1):

import numpy as np

arr1 = np.array([[1, 2], [3, 4]])

arr2 = np.array([[5, 6], [7, 8]])

arr = np.concatenate((arr1, arr2), axis=1)

print(arr)