# How to Use the Numpy concatenate() Function in Python

09/15/2021

Contents

In this article, you will learn how to use the Numpy concatenate() function in Python.

## Numpy concatenate() Function

The numpy.concatenate() function is used to concatenate two or more arrays along a specified axis.

##### Syntax
``numpy.concatenate((array1, array2, ...), axis=0, out=None)``
##### Parameters
• `array1, array2, ...`: Two or more arrays to be concatenated. They must have the same shape, except in the dimension corresponding to the axis argument.
• `axis`: The axis along which the arrays will be joined. Default is 0.
• `out`: If provided, the result will be stored in this array.
##### Example
``````import numpy as np

# Concatenate two 1D arrays
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.concatenate((a, b))
print(c)
# Output: [1 2 3 4 5 6]

# Concatenate two 2D arrays along axis=0
a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6]])
c = np.concatenate((a, b), axis=0)
print(c)  # Output: [[1 2]
#          [3 4]
#          [5 6]]

# Concatenate two 2D arrays along axis=1
a = np.array([[1, 2], [3, 4]])
b = np.array([[5], [6]])
c = np.concatenate((a, b), axis=1)
print(c)  # Output: [[1 2 5]
#          [3 4 6]]
``````

In the first example, two 1D arrays are concatenated into a single 1D array.

In the second example, two 2D arrays are concatenated along axis=0, which results in a 3×2 array.

In the third example, two 2D arrays are concatenated along axis=1, which results in a 2×3 array.