Min and Max in Python - HackerRank Solution
Min and Max in Python - HackerRank Solution
Problem :
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.
Task :
You are given a 2-D array with dimensions NXM.
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.
Sample Input :
4 2 2 5 3 7 1 3 4 0
Sample Output :
3
Explanation :
The min along axis 1 = [2, 3, 1, 0]
The max of [2, 3, 1, 0]= 3
The max of [2, 3, 1, 0]= 3
Solution :
1 2 3 4 5 6 7 8 9 | # Min and Max in Python - Hacker Rank Solution # Python 3 # Min and Max in Python - Hacker Rank Solution START import numpy N, M = map(int, input().split()) storage = numpy.array([input().split() for _ in range(N)],int) print(numpy.max(numpy.min(storage, axis=1), axis=0)) # Min and Max in Python - Hacker Rank Solution END |
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