# Concatenate in Python – HackerRank Solution

Two or more arrays can be concatenated together using the concatenate function with a tuple of the arrays to be joined:

```import numpy
array_1 = numpy.array([1,2,3])
array_2 = numpy.array([4,5,6])
array_3 = numpy.array([7,8,9])
print numpy.concatenate((array_1, array_2, array_3))
#Output
[1 2 3 4 5 6 7 8 9]
```

if an array has more than one dimension, it is possible to specify the axis along which multiple arrays are concatenated. By default, it is along the first dimension.

```import numpy
array_1 = numpy.array([[1,2,3],[0,0,0]])
array_2 = numpy.array([[0,0,0],[7,8,9]])
print numpy.concatenate((array_1, array_2), axis = 1)
#Output
[[1 2 3 0 0 0]
[0 0 0 7 8 9]]
```

You are given two integer arrays of size NXP and MXP ( N & M are rows, and P is the column). Your task is to concatenate the arrays along axis 0.

#### Input Format :

The first line contains space separated integers N, M and P.
The next N lines contains the space separated elements of the P columns.After that, the next M lines contains the space separated elements of the P columns.

#### Output Format :

Print the concatenated array of size (N+M)XP.

```4 3 2
1 2
1 2
1 2
1 2
3 4
3 4
3 4
```

#### Sample Output :

```[[1 2]
[1 2]
[1 2]
[1 2]
[3 4]
[3 4]
[3 4]]```

### Concatenate in Python – HackerRank Solution

```import numpy
P, N, M = map(int,input().split())
A = numpy.array([input().split() for _ in range(P)],int)
B = numpy.array([input().split() for _ in range(N)],int)
print(numpy.concatenate((A, B), axis = 0))```

Disclaimer: The above Problem (Concatenate in Python – HackerRank Solution) is generated by Hackerrank but the Solution is Provided by Chase2Learn. This tutorial is only for Educational and Learning purposes. Authority if any of the queries regarding this post or website fill the following contact form thank you.