numpy_concatenate.py

"""
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 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.

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]] 

"""

import numpy
k = map(int,raw_input().split())
l,m = [ map(int,raw_input().split()) for _ in xrange(k[0]) ],[ map(int,raw_input().split()) for _ in xrange(k[1]) ]
array_1,array_2 = numpy.array(l),numpy.array(m)

print numpy.concatenate((array_1, array_2), axis = 0)