Mean, Var, and Std in Python HackerRank Solution

Hello coders, In this post, you will learn how to solve Mean, Var, and Std in Python HackerRank Solution. This problem is a part of the Python Hacker Rank series.

Mean, Var, and Std in Python HackerRank Solution

Problem

meanThe mean tool computes the arithmetic mean along the specified axis.

import numpy
my_array = numpy.array([ [1, 2], [3, 4] ])
print numpy.mean(my_array, axis = 0)        #Output : [ 2.  3.]
print numpy.mean(my_array, axis = 1)        #Output : [ 1.5  3.5]
print numpy.mean(my_array, axis = None)     #Output : 2.5
print numpy.mean(my_array)                  #Output : 2.5

By default, the axis is None. Therefore, it computes the mean of the flattened array.
varThe var tool computes the arithmetic variance along the specified axis.

import numpy
my_array = numpy.array([ [1, 2], [3, 4] ])
print numpy.var(my_array, axis = 0)         #Output : [ 1.  1.]
print numpy.var(my_array, axis = 1)         #Output : [ 0.25  0.25]
print numpy.var(my_array, axis = None)      #Output : 1.25
print numpy.var(my_array)                   #Output : 1.25

By default, the axis is None. Therefore, it computes the variance of the flattened array. stdThe std tool computes the arithmetic standard deviation along the specified axis.

import numpy
my_array = numpy.array([ [1, 2], [3, 4] ])
print numpy.std(my_array, axis = 0)         #Output : [ 1.  1.]
print numpy.std(my_array, axis = 1)         #Output : [ 0.5  0.5]
print numpy.std(my_array, axis = None)      #Output : 1.11803398875
print numpy.std(my_array)                   #Output : 1.11803398875

By default, the axis is None. Therefore, it computes the standard deviation of the flattened array.

Task :

You are given a 2-D array of size NXM.
Your task is to find:The mean along axis 1The var along axis 0The std along axis

Input Format :

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

Output Format :

First, print the mean.
Second, print the var.
Third, print the std.

Sample Input :

2 2
1 2
3 4

Sample Output :

[ 1.5  3.5]
[ 1.  1.]
1.11803398875

Mean, Var, and Std in Python – HackerRank Solution

import numpy
N,M = map(int, input().split())
l = []
for i in range(N):
    a = list(map(int, input().split()))
    l.append(a)
l = numpy.array(l)
numpy.set_printoptions(legacy='1.13')
print(numpy.mean(l, axis = 1))
print(numpy.var(l, axis = 0))
print(numpy.std(l))

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