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**Introduction To Python**

**Python **is a widely-used, interpreted, **object-oriented, and high-level programming** language with dynamic semantics, used for general-purpose programming. It was created by **Guido van Rossum**, and first released on **February 20, 1991**.

**Python **is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. It is also used to create various machine learning algorithm, and helps in Artificial Intelligence. Python is a general purpose language, meaning it can be used to create a variety of different programs and isn’t specialized for any specific problems. This versatility, along with its beginner-friendliness, has made it one of the most-used programming languages today. A survey conducted by industry analyst firm **RedMonk **found that it was the most popular programming language among developers in **2020**.

** Link for the Problem** – Mean, Var, and Std in Python – HackerRank Solution

Mean, Var, and Std in Python – HackerRank Solution

**Problem:**

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

importnumpymy_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.

importnumpymy_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. **std**The std tool computes the arithmetic standard deviation along the specified axis.

importnumpymy_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 :

221234

#### Sample Output :

[1.53.5] [1.1.]1.11803398875

#### 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.

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))