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Home Interviews How to use NumPy Joining Array? – MindStick
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1 Answers

ICSM Computer
ICSM Computer 13 Nov 2025
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Easy guide to joining arrays in NumPy (combining two or more arrays into one).
NumPy provides multiple ways to join arrays depending on the shape and how you want to merge them.

1. Using np.concatenate()

This is the most common way to join arrays.

Example — Join 1D Arrays

import numpy as np

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

result = np.concatenate((a, b))
print(result)

Output:

[1 2 3 4 5 6]

Example — Join 2D Arrays (Row-wise)

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

result = np.concatenate((a, b), axis=0)
print(result)

Output:

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

Example — Join 2D Arrays (Column-wise)

result = np.concatenate((a, b), axis=1)
print(result)

Output:

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

2. Using np.stack()

Creates a new dimension.

Example:

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

result = np.stack((a, b), axis=0)
print(result)

Output:

[[1 2 3]
 [4 5 6]]

Here, arrays are stacked into 2 rows.

3. Using np.hstack() (Horizontal Stack)

Joins arrays side by side.

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

result = np.hstack((a, b))
print(result)

Output:

[1 2 3 4 5 6]

For 2D arrays, it stacks column-wise.

4. Using np.vstack() (Vertical Stack)

Joins arrays top to bottom.

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

result = np.vstack((a, b))
print(result)

Output:

[[1 2 3]
 [4 5 6]]

5. Using np.dstack() (Depth Stack)

Stacks arrays into depth (3rd dimension).

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

result = np.dstack((a, b))
print(result)

Output:

[[[1 4]
  [2 5]
  [3 6]]]

Summary Table

Function Behavior
concatenate() Join along existing axis
stack() Join but create a new axis
hstack() Join horizontally
vstack() Join vertically
dstack() Join depth-wise (3D)
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