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Home Forums How to work NumPy Splitting Array? – MindStick
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1 Answers

Anubhav Sharma
Anubhav Sharma 25 Nov 2025
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NumPy provides multiple functions to split an array into multiple sub-arrays:

1. np.split

Splits an array into equal parts (unless you specify explicit indices).

1. Using np.split with equal splits

import numpy as np

arr = np.array([1,2,3,4,5,6])

result = np.split(arr, 3)
print(result)

Output:

[array([1, 2]), array([3, 4]), array([5, 6])]
  • Here we split into 3 equal parts, so each part contains 2 elements.
  • If the array cannot be split equally, NumPy throws an error.

2. Using np.split with index positions

You can specify split positions:

arr = np.array([10, 20, 30, 40, 50, 60])

result = np.split(arr, [2, 4])
print(result)

Output:

[array([10, 20]), array([30, 40]), array([50, 60])]

Explanation:

  • Split at index 2 → [10,20]
  • Split at index 4 → [30,40]
  • Remaining → [50,60]

2. np.array_split (more flexible)

Unlike np.split, it allows uneven splits.

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

result = np.array_split(arr, 3)
print(result)

Output:

[array([1, 2, 3]), array([4, 5]), array([6, 7])]

3. Splitting a 2D Array

Horizontal split (hsplit) → split columns

arr = np.array([[1,2,3],
                [4,5,6]])

result = np.hsplit(arr, 3)
print(result)

Output:

[array([[1],
       [4]]),
 array([[2],
       [5]]),
 array([[3],
       [6]])]

Vertical split (vsplit) → split rows

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

result = np.vsplit(arr, 3)
print(result)

Output:

[array([[1, 2, 3]]),
 array([[4, 5, 6]]),
 array([[7, 8, 9]])]

4. Depth split (dsplit) → split along 3D depth axis

arr = np.arange(12).reshape(2,2,3)

print(np.dsplit(arr, 3))

Summary Table

Function Use
np.split() Strict equal splits or split by index
np.array_split() Allows uneven splits
np.hsplit() Split columns
np.vsplit() Split rows
np.dsplit() Split along the depth of a 3D array
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