Inorder Traversal in Binary Tree YASH PAL, 3 June 202028 June 2025 In the Inorder traversal of the binary tree, we first visit the left subtree of the root node, and then we visit the root node and after that, we visit the right subtree of the root node.Properties of Inorder traversalTraverse the left subtree of the root in InorderVisit the root nodeTraverse the right subtree of the root in Inorderlet’s understand it with an example let’s say we have a binary tree as you see in the image given below.First, we need to divide the whole tree into subtrees as you see in the given image above. and then we start traversing the tree.as you see first we visit the left subtree of the root node in inorder. so the root node is P and its left subtree is B but in subtree B, there is also a left subtree D so we first start traversing with subtree D. In the subtree, there is no left subtree so we first visit the left node and then the root node, and then the right node.so the inorder traversal of subtree D is T S Q and inorder of subtree B is D A E and substitute the value of subtree D so the inorder is T S Q A E P F Cnow find the inorder of subtree E and the inorder of E is E D so the inorder isT S Q A E D P F Cnow go to the root node P so the inorder isT S Q A E D P F Cnow find the inorder of subtree C but in subtree C, there is also left subtree F and right subtree G.so first we need to find the inorder of the F subtree because it’s a left subtree and in inorder, the left subtree comes first, and then the root node and right node.so the inorder of subtree F is M so the inorder of subtree C isM X Gnow we find the inorder of subtree G so the inorder of subtree is C Rso the inorder of subtree C isM X C Rnow we substitute the inorder of right subtree C into the so the inorder of the binary tree isT S Q A E D P M X C RProgram to find the inorder of binary trees using Python.from collections import deque class Node: def __init__(self, value): self.info = value self.lchild = None self.rchild = None class BinaryTree: def __init__(self): self.root = None def is_empty(self): return self.root is None def display(self): self._display(self.root, 0) print() def _display(self,p,level): if p is None: return self._display(p.rchild, level+1) print() for i in range(level): print(" ", end='') print(p.info) self._display(p.lchild, level+1) def preorder(self): self._preorder(self.root) print() def _preorder(self,p): if p is None: return print(p.info, " ", end='') self._preorder(p.lchild) self._preorder(p.rchild) def inorder(self): self._inorder(self.root) print() def _inorder(self,p): if p is None: return self._inorder(p.lchild) print(p.info," ", end='') self._inorder(p.rchild) def postorder(self): self._postorder(self.root) print() def _postorder(self,p): if p is None: return self._postorder(p.lchild) self._postorder(p.rchild) print(p.info," ",end='') def level_order(self): if self.root is None: print("Tree is empty") return qu = deque() qu.append(self.root) while len(qu) != 0: p = qu.popleft() print(p.info + " ", end='') if p.lchild is not None: qu.append(p.lchild) if p.rchild is not None: qu.append(p.rchild) def height(self): return self._height(self.root) def _height(self,p): if p is None: return 0 hL = self._height(p.lchild) hR = self._height(p.rchild) if hL > hR: return 1 + hL else: return 1 + hR def create_tree(self): self.root = Node('p') self.root.lchild = Node('Q') self.root.rchild = Node('R') self.root.lchild.lchild = Node('A') self.root.lchild.rchild = Node('B') self.root.rchild.lchild = Node('X') ########################## bt = BinaryTree() bt.create_tree() bt.display() print() print("Preorder : ") bt.preorder() print("") print("Inorder : ") bt.inorder() print() print("Postorder : ") bt.postorder() print() print("Level order : ") bt.level_order() print() print("Height of tree is ", bt.height()) Computer Science Tutorials Data Structures Tutorials computer scienceData Structure