## Algorithm

Problem Name: Python - Concatenate

In this HackerRank Functions in PYTHON problem solution,

Concatenate

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 N *  M and M * P(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.

Output Format

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

Sample Input

``````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]]
``````

## Code Examples

### #1 Code Example with Python Programming

```Code - Python Programming```

``````
import numpy as np

shape = list(input().strip().split(" "))
shape1 = np.array(shape,int)
mat1 = []
for _ in range(shape1[0]+shape1[1]):
mat = list(input().strip().split())
mat1.append(mat)

print(np.array(mat1,int))
``````
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