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## 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:

**mean**The mean tool computes the arithmetic mean along the specified axis.

import numpymy_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.

**var**The 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

## HackerRank Solutions

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

import numpymy_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.

### 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

## HackerRank Solutions

### 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.

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