Splitting Arrays

Definition: Splitting is the opposite of joining — it breaks one array into several smaller ones. np.array_split divides an array into a chosen number of parts.

Example 1 — split into equal parts

import numpy as np
a = np.array([1, 2, 3, 4, 5, 6])
parts = np.array_split(a, 3)
print(parts)        # [array([1,2]), array([3,4]), array([5,6])]
print(parts[0])     # the first chunk

Example 2 — uneven splits are handled

Unlike strict split, array_split copes when the array does not divide evenly:

import numpy as np
a = np.array([1, 2, 3, 4, 5])
print(np.array_split(a, 3))   # sizes 2, 2, 1

Splitting a 2D array

import numpy as np
b = np.arange(1, 7).reshape(3, 2)
print(np.array_split(b, 3))   # one row per part

💡 Tip: splitting is useful for breaking a dataset into batches — for example, dividing data for training and testing.