**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 :

` ````
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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