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# Binary Tree

#### In this tutorial, you will learn about binary tree and its different types. Also, you will find working examples of binary tree in Python.

A binary tree is a tree data structure in which each parent node can have at most two children.

For example: In the image below, each element has at most two children.

## Types of Binary Tree

### Full Binary Tree

A full Binary tree is a special type of binary tree in which every parent node/internal node has either two or no children.

### Perfect Binary Tree

A perfect binary tree is a type of binary tree in which every internal node has exactly two child nodes and all the leaf nodes are at the same level.

### Complete Binary Tree

A complete binary tree is just like a full binary tree, but with two major differences

- Every level must be completely filled
- All the leaf elements must lean towards the left.
- The last leaf element might not have a right sibling i.e. a complete binary tree doesn’t have to be a full binary tree.

### Degenerate or Pathological Tree

A degenerate or pathological tree is the tree having a single child either left or right.

### Skewed Binary Tree

A skewed binary tree is a pathological/degenerate tree in which the tree is either dominated by the left nodes or the right nodes. Thus, there are two types of skewed binary tree: **left-skewed binary tree** and **right-skewed binary tree**.

### Balanced Binary Tree

It is a type of binary tree in which the difference between the left and the right subtree for each node is either 0 or 1.

## Binary Tree Representation

A node of a binary tree is represented by a structure containing a data part and two pointers to other structures of the same type.

```
struct node
{
int data;
struct node *left;
struct node *right;
};
```

## Python Examples

```
/* Binary Tree in Python */
class Node:
def __init__(self, key):
self.left = None
self.right = None
self.val = key
/* Traverse preorder */
def traversePreOrder(self):
print(self.val, end=' ')
if self.left:
self.left.traversePreOrder()
if self.right:
self.right.traversePreOrder()
/* Traverse inorder */
def traverseInOrder(self):
if self.left:
self.left.traverseInOrder()
print(self.val, end=' ')
if self.right:
self.right.traverseInOrder()
/* Traverse postorder */
def traversePostOrder(self):
if self.left:
self.left.traversePostOrder()
if self.right:
self.right.traversePostOrder()
print(self.val, end=' ')
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
print("Pre order Traversal: ", end="")
root.traversePreOrder()
print("nIn order Traversal: ", end="")
root.traverseInOrder()
print("nPost order Traversal: ", end="")
root.traversePostOrder()
```

## Binary Tree Applications

- For easy and quick access to data
- In router algorithms
- To implement heap data structure
- Syntax tree

# Python Example for Beginners

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There are two sides to machine learning:

**Practical Machine Learning:**This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.**Theoretical Machine Learning**: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

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