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     Hey if you new to programming and you came straight to Data Structures and Algorithms. And you have selected the c++ as your partner in this journey. Well then don't worry Data Structures and Algorithms are not hard to understand with c++ .      I think it is easy in c++ to learn Data Structures and Algorithms. It's simple object oriented way of doing things. And If you know even a little bit of OOP you will be able to understand it very well. Binary Tree In C++     In this article we making a binary tree in C++ OOP way . So this file will have a node class which will be our node or vertex. And a binary tree class which will be the collection of these nodes or vertex. Where main operations of the binary will be performed.     Below are some methods that we will implement in the binary tree. insert() - to insert the data in the tree printInorder() - to print the tree inorder traversal printPreOrder() - to print the tree in PreOrde...

1. What is tree?      - A Tree is  a finite set of one or more nodes such that : There is a specially designated node called the root.  Remaining nodes are partitioned into (n >= 0) disjoint sets T1, T2, ..., Tn where each of these sets is a tree. Each T1, T2, T3 .... Tn are called sbu trees of the root. 2. Leaf Node     - In a tree data structure, the node which does not have a child is called as Leaf Node. 3. Height of tree     - In a tree data structure , the total number of edges from leaf node to a particular node in the longest path is called as height of the Node. In a tree, height of the root node is said to be height of the tree. 4.  Depth of tree      - In a tree data structure, the total number of edges from root node to a particular node is called as DEPTH of that Node. In a tree, the total number of edges from root node a to a leaf node in the longest path is said to be Depth of the tree. 5.  Node...

      Hey in the article we are looking at a coding challenge problem. You might have come across this it is called finding the lowest common ancestor in a binary tree.      So we will find the solution to this problem in python. Let's start. The answer is simple we have to visit every node and check if its child is same as it is asked if so then you return the node and we repeat this process for subtrees of  the tree and then if left and right node exit we return it. to the top. code:  class Node :     def __init__ (self,data):         self . data = data         self . left = None         self . right = None class binaryTree :     def __init__ (self):         self . root = None     #inserts a node in binary tree     def insert (self,data):         if ( self . root == None ):     ...