Mean, Var, and Std in Python – HackerRank Solution

Mean, Var, and Std in Python – HackerRank Solution

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))

Disclaimer: The above Problem (Mean, Var, and Std in Python ) is generated by Hackerrank but the Solution is Provided by Chase2Learn. This tutorial is only for Educational and Learning purposes. Authority if any of the queries regarding this post or website fill the following contact form thank you.

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