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HackerRank Solutions : Hi Programmers/Coders, Today we will share arrangements of Mean, Var, and Std in Python – HackerRank Solutions At Each Problem with Successful accommodation with all Test Cases Passed, you will get a score or stamps. What’s more, subsequent to taking care of greatest issues, you will get stars. This will feature your profile to the scouts.

in this article , you will track down the answer forMean, Var, and Std in Python – HackerRank Solutions. We are giving the right and tried arrangements of coding issues present on HackerRank. In the event that you can’t tackle any issue, then, at that point, you can take help from our Blog.

Introduction To Python

HackerRank Solutions: Python is a broadly utilized, deciphered, object-situated, and significant level programming language with dynamic semantics, utilized for universally useful programming. It was made by Guido van Rossum, and first delivered on February 20, 1991.

Python is a PC programming language frequently used to construct sites and programming, computerize errands, and direct information examination. It is additionally used to make different AI calculation, and helps in Artificial Intelligence. Python is a broadly useful language, meaning it very well may be utilized to make a wide range of projects and isn’t particular for a particular issues. This flexibility, alongside its novice cordiality, has made it one of the most-utilized programming dialects today. An overview led by industry expert firm RedMonk observed that it was the most famous programming language among designers in 2020.

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Mean, Var, and Std in Python – HackerRank Solutions

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

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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.