=====Function Descriptions=====
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 : 1.118033988749895
print numpy.std(my_array)                   #Output : 1.118033988749895
By default, the axis is None. Therefore, it computes the standard deviation of the flattened array.
=====Problem Statement=====
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 M space separated integers.
=====Output Format=====
First, print the mean.
Second, print the var.
Third, print the std.
import numpy as np

n, m = [int(x) for x in input().strip().split()]
array = np.array([[int(x) for x in input().strip().split()] for _ in range(n)], dtype = float)
print(np.mean(array, axis = 1))
print(np.var(array, axis = 0))
print(np.std(array))
import numpy as np

n, m = [int(x) for x in input().strip().split()]
array = np.array([[int(x) for x in input().strip().split()] for _ in range(n)], dtype = float)
print(np.mean(array, axis = 1))
print(np.var(array, axis = 0))
print(np.std(array))