Mean, Var, and Std python


Problem Statement :


mean

The 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.

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
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 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 N X M.
Your task is to find:

The mean along axis 1
The var along axis 0
The std along axis None


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.


Solution :



title-img 


                            Solution in C :

import numpy

n,m=map(int,input().split())

a=numpy.array([list(map(int,input().split())) for i in range(n)])
print(numpy.mean(a,axis=1))
print(numpy.var(a,axis=0))
print(numpy.std(a,None))








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