Min and Max - Hacker Rank Solution

Min and Max - Hacker Rank Solution

We can solve this using the min tool along axis  and then using max.

import numpy

N, M = map(int, raw_input().split())

my_array = numpy.array([ map(int, raw_input().split()) for i in range(N) ])

print numpy.max(numpy.min(my_array, axis = 1))