# -*- coding: utf-8 -*-
"""
Created on Fri Mar  1 18:19:41 2019

@author: Ham

HackerRanch Challenge: Mean, Var and Std

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 NxM.
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 N 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

"""

import numpy

# ignoring 2nd int of 1st line, M
a = [list(map(int, input().strip().split()))
     for _ in range(int(input().strip().split()[0]))]
# I cheated: got the printoptions from Discussion
numpy.set_printoptions(legacy='1.13')
print(numpy.mean(a, axis=1))
print(numpy.var(a, axis=0))
print(numpy.std(a))
