Tree represents the nodes connected by edges. It is a non-linear data structure. It has the following properties.

One node is marked as Root node.

Every node other than the root is associated with one parent node.

Each node can have an arbiatry number of chid node.

We create a tree data structure in python by using the concept os node discussed earlier. We designate one node as root node and then add more
nodes as child nodes. Below is program to create the root node.

Create Root

We just create a Node class and add assign a value to the node. This becomes tree with only a root node.

To insert into a tree we use the same node class created above and add a insert class to it. The insert class compares the value of
the node to the parent node and decides to add it as a left node or a right node. Finally the PrintTree class is used to print the tree.

class Node:
def __init__(self, data):
self.left = None
self.right = None
self.data = data
def insert(self, data):
# Compare the new value with the parent node
if self.data:
if data < self.data:
if self.left is None:
self.left = Node(data)
else:
self.left.insert(data)
elif data > self.data:
if self.right is None:
self.right = Node(data)
else:
self.right.insert(data)
else:
self.data = data
# Print the tree
def PrintTree(self):
if self.left:
self.left.PrintTree()
print( self.data),
if self.right:
self.right.PrintTree()
# Use the insert method to add nodes
root = Node(12)
root.insert(6)
root.insert(14)
root.insert(3)
root.PrintTree()

When the above code is executed, it produces the following result −

3 6 12 14

Traversing a Tree

The tree can be traversed by deciding on a sequence to visit each node. As we can clearly see we can start at a node then visit the left sub-tree first and right sub-tree next.
Or we can also visit the right sub-tree first and left sub-tree next. Accordingly there are different names for these tree traversal methods.
We study them in detail in the chapter implementing the tree traversal algorithms here.
Tree Traversal Algorithms

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Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..

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Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..

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Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..

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Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..

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