HackerRank Python Solution - Numpy Topic - Concatenate

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 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 contain the space-separated elements of the P columns. After that, the next M lines contain the space-separated elements of the P columns.

Output Format:

Print the concatenated array of size (N + M) x 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]] 

Solution:

import numpy as np

n,m,p = map(int,input().split())

arr1 = np.array([input().split() for _ in range(n)],int)
arr2 = np.array([input().split() for _ in range(m)],int)

print(np.concatenate((arr1,arr2),axis=0))
  

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