Left Side View of Binary Tree in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Left Side View of a Binary Tree?

It is the set of nodes visible when the tree is seen from the left side. Only the first node at each level from the left is included.

beginner

Which tree traversal method is commonly used to find the Left Side View of a Binary Tree?

Level order traversal (Breadth-First Search) is commonly used because it processes nodes level by level, making it easy to pick the first node at each level.

beginner

In the Left Side View, why do we pick the first node at each level?

Because the first node encountered at each level from left to right is the one visible from the left side, as it blocks nodes behind it.

intermediate

What data structure helps to implement the Left Side View algorithm efficiently?

A queue helps to perform level order traversal, allowing us to process nodes level by level and pick the first node at each level.

intermediate

How does recursion help in finding the Left Side View of a Binary Tree?

Recursion with depth tracking can be used to visit nodes pre-order (root-left-right) and record the first node visited at each depth, which forms the left view.

What does the Left Side View of a binary tree represent?

A Nodes visible when looking from the right side

B Nodes with only left children

C All leaf nodes

D Nodes visible when looking from the left side

The left side view shows nodes visible from the left side of the tree.

Which traversal is best suited to find the Left Side View of a binary tree?

A Level order traversal

B Inorder traversal

C Postorder traversal

D Preorder traversal

Level order traversal processes nodes level by level, making it easy to pick the first node at each level.

In a recursive approach, what do we track to find the left side view?

A Depth or level of nodes

B Number of children

C Sum of node values

D Height of the tree

Tracking depth helps to record the first node visited at each level.

What data structure is commonly used in iterative solutions for the Left Side View?

A Set

B Stack

C Queue

D Map

A queue supports level order traversal by processing nodes level by level.

If a binary tree has only right children, what will the Left Side View contain?

A Only the root node

B All nodes in the tree

C No nodes

D Only leaf nodes

Since all nodes are visible from the left side in a right-skewed tree, the left side view includes all nodes.

Explain how to find the Left Side View of a Binary Tree using level order traversal.

Think about how you see the tree from left side level by level.

Describe a recursive method to get the Left Side View of a Binary Tree.

Consider pre-order traversal with depth tracking.

Practice

1. What does the Left Side View of a binary tree represent?

easy

A. Nodes visible when the tree is viewed from the right side

B. Nodes at the deepest level of the tree

C. All leaf nodes of the tree

D. Nodes visible when the tree is viewed from the left side

Solution

1. Step 1: Understand the view perspective

   The left side view shows nodes visible when looking at the tree from the left side.

2. Step 2: Identify visible nodes

   Only the first node at each level from the left is visible in this view.

3. Final Answer:

   Nodes visible when the tree is viewed from the left side -> Option D

4. Quick Check:

   Left side view = nodes visible from left [OK]

Hint: Left side view shows first node at each level from left [OK]

Common Mistakes:

• Confusing left side view with right side view
• Thinking it shows all leaf nodes
• Assuming it shows deepest nodes only

2. Which of the following Python code snippets correctly initializes an empty list to store the left side view nodes?

easy

A. left_view = ()

B. left_view = {}

C. left_view = []

D. left_view = set()

Solution

1. Step 1: Identify the correct data structure

   We need a list to store nodes in order, so an empty list is best.

2. Step 2: Check syntax for list initialization

   Using square brackets [] creates an empty list in Python.

3. Final Answer:

   left_view = [] -> Option C

4. Quick Check:

   Empty list = [] [OK]

Hint: Use [] to create empty list for ordered nodes [OK]

Common Mistakes:

• Using {} which creates a dictionary, not a list
• Using () which creates a tuple, not a list
• Using set() which is unordered

3. What is the output of the following code that prints the left side view of the given binary tree?

class Node:
    def __init__(self, val):
        self.val = val
        self.left = None
        self.right = None

def left_side_view(root):
    result = []
    def dfs(node, level):
        if not node:
            return
        if level == len(result):
            result.append(node.val)
        dfs(node.left, level + 1)
        dfs(node.right, level + 1)
    dfs(root, 0)
    return result

root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.right = Node(4)
root.right.right = Node(5)

print(left_side_view(root))

medium

A. [1, 2, 3]

B. [1, 2, 4]

C. [1, 3, 5]

D. [1, 4, 5]

Solution

1. Step 1: Trace DFS traversal and level checks

   At level 0, node 1 is added. At level 1, node 2 is added (left child). At level 2, node 4 is added (left child's right child).

2. Step 2: Confirm nodes added only once per level

   Right children at each level are ignored if left child exists at that level.

3. Final Answer:

   [1, 2, 4] -> Option B

4. Quick Check:

   Left side view nodes = [1, 2, 4] [OK]

Hint: Add node if level equals result length during DFS [OK]

Common Mistakes:

• Adding right child nodes before left child nodes
• Appending nodes multiple times per level
• Confusing left and right children order

4. Find the error in the following code that attempts to print the left side view of a binary tree:

def left_side_view(root):
    result = []
    def dfs(node, level):
        if node is None:
            return
        if level < len(result):
            result.append(node.val)
        dfs(node.left, level + 1)
        dfs(node.right, level + 1)
    dfs(root, 0)
    return result

medium

A. The condition should be 'level == len(result)', not 'level < len(result)'

B. The base case should check 'if node' instead of 'if node is None'

C. The recursive calls should swap left and right children

D. The function should return 'result' inside the dfs function

Solution

1. Step 1: Analyze the condition for adding nodes

   The code uses 'level < len(result)' which is incorrect because nodes should be added only when level equals the current result length.

2. Step 2: Correct the condition to add nodes once per level

   Changing condition to 'level == len(result)' ensures only the first node at each level is added.

3. Final Answer:

   The condition should be 'level == len(result)', not 'level < len(result)' -> Option A

4. Quick Check:

   Use '==' to add first node per level [OK]

Hint: Add node only when level equals result length [OK]

Common Mistakes:

• Using '<' instead of '==' in condition
• Returning result inside recursive function
• Swapping left and right child calls unnecessarily

5. Given a binary tree, how would you modify the standard left side view algorithm to return the left side view nodes in reverse order (bottom to top)?

hard

A. Perform the usual left side view traversal, then reverse the result list before returning

B. Traverse the tree from right to left instead of left to right

C. Add nodes to the result list only if they are leaf nodes

D. Use a queue and perform level order traversal from right to left

Solution

1. Step 1: Perform standard left side view traversal

   Use DFS or BFS to collect the first node at each level from left to right.

2. Step 2: Reverse the collected list

   After traversal, reverse the list to get nodes from bottom to top.

3. Final Answer:

   Perform the usual left side view traversal, then reverse the result list before returning -> Option A

4. Quick Check:

   Reverse after left side view traversal [OK]

Hint: Reverse the left side view list after traversal [OK]

Common Mistakes:

• Changing traversal order instead of reversing result
• Collecting leaf nodes only
• Using right to left traversal which gives wrong nodes