Algorithm


Problem Name: Python - Concatenate

Problem Link: https://www.hackerrank.com/challenges/np-concatenate/problem?isFullScreen=true   

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]]    

 


 

Task

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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Demonstration


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