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## NumPy np.c_

The NumPy np.c_ is part of the NumPy’s indexing routines that allow you to concatenate an array along the second axis.

Let us explore how this routine works and how we can use it.

## Syntax

The syntax of the numpy c_ routine is as shown below:

numpy.c_[arrays]

## Return Value

The routine does not take any parameters except the arrays that you need to concatenate.

It will then return the concatenated array along the second axis.

## Example Illustration

The example below illustrates how to use the np.c_ to concatenate two arrays.

# import numpy
import numpy as np
# create an array
arr1 = np.array([1,2,3])
arr2 = np.array([7,8,9])
print(np.c_[arr1, arr2])

In this example, the np.c_ routine takes the arrays and concatenates them along the second axis.

NOTE: When talking about the second axis, we refer to the axis=1 or the column axis.

The code above should return an array as:

[[1 7]
[2 8]
[3 9]]

In this case, the np.c_ takes two one-dimensional arrays and concatenates them to form a two-dimensional array.

## Example #2

Let us see what happens when we apply the routine in 2d arrays.

arr1 = np.array([[1,2,3,4], [5,6,7,8]])
arr2 = np.array([[9,10,11,12], [13,14,15,16]])
print(np.c_[arr1, arr2])

The code snippet above should return:

[[ 1  2  3  4  9 10 11 12]
[ 5  6  7  8 13 14 15 16]]