# Min and Max python

### Problem Statement :

```min

The tool min returns the minimum value along a given axis.

import numpy

my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])

print numpy.min(my_array, axis = 0)         #Output : [1 0]
print numpy.min(my_array, axis = 1)         #Output : [2 3 1 0]
print numpy.min(my_array, axis = None)      #Output : 0
print numpy.min(my_array)                   #Output : 0
By default, the axis value is None. Therefore, it finds the minimum over all the dimensions of the input array.

max

The tool max returns the maximum value along a given axis.

import numpy

my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])

print numpy.max(my_array, axis = 0)         #Output : [4 7]
print numpy.max(my_array, axis = 1)         #Output : [5 7 3 4]
print numpy.max(my_array, axis = None)      #Output : 7
print numpy.max(my_array)                   #Output : 7
By default, the axis value is None. Therefore, it finds the maximum over all the dimensions of the input array.

You are given a 2-D array with dimensions N X M.
Your task is to perform the min function over axis 1 and then find the max of that.

Input Format

The first line of input contains the space separated values of N and M.
The next N lines contains M space separated integers.

Output Format

Compute the min along axis 1 and then print the max of that result.```

### Solution :

```                            ```Solution in C :

import numpy

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

lista=[list(map(int,input().split())) for i in range(n)]

ar=numpy.array(lista)

print(max(numpy.min(ar,axis=1)))```
```

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