# 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.

You are given a 2-D array of size N X M.

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))```
```

## Delete a Node

Delete the node at a given position in a linked list and return a reference to the head node. The head is at position 0. The list may be empty after you delete the node. In that case, return a null value. Example: list=0->1->2->3 position=2 After removing the node at position 2, list'= 0->1->-3. Function Description: Complete the deleteNode function in the editor below. deleteNo

## Print in Reverse

Given a pointer to the head of a singly-linked list, print each data value from the reversed list. If the given list is empty, do not print anything. Example head* refers to the linked list with data values 1->2->3->Null Print the following: 3 2 1 Function Description: Complete the reversePrint function in the editor below. reversePrint has the following parameters: Sing

Given the pointer to the head node of a linked list, change the next pointers of the nodes so that their order is reversed. The head pointer given may be null meaning that the initial list is empty. Example: head references the list 1->2->3->Null. Manipulate the next pointers of each node in place and return head, now referencing the head of the list 3->2->1->Null. Function Descriptio