Largest Rectangle in Histogram Using Stack in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main idea behind using a stack to find the largest rectangle in a histogram?

Use a stack to keep track of bars in increasing height order. When a smaller bar appears, calculate areas for taller bars popped from the stack to find the largest rectangle.

beginner

Why do we push the index of bars onto the stack instead of their heights?

Storing indices helps calculate the width of rectangles easily by using the current index and the index on the stack top.

intermediate

What triggers the calculation of area for bars in the stack during the algorithm?

When the current bar is shorter than the bar at the top of the stack, we pop from the stack and calculate the area for the popped bar.

intermediate

How do you calculate the width of the rectangle when popping a bar from the stack?

Width = current index - index of new stack top - 1. If stack is empty, width = current index.

beginner

What is the time complexity of the Largest Rectangle in Histogram algorithm using a stack?

O(n), because each bar is pushed and popped at most once.

What data structure is used to solve the Largest Rectangle in Histogram problem efficiently?

A Linked List

B Queue

C Stack

D Hash Map

A stack helps track bars in increasing height order to calculate areas efficiently.

When do we pop bars from the stack during the algorithm?

A When the current bar is shorter than the top of the stack

B When the stack is empty

C At the end of the array only

D When the current bar is taller than the top of the stack

We pop bars when the current bar is shorter to calculate areas for taller bars.

What does the stack store in the Largest Rectangle in Histogram algorithm?

A Indices of bars

B Heights of bars

C Widths of bars

D Areas of rectangles

Stack stores indices to calculate widths easily.

How is the width calculated when popping a bar from the stack?

A Popped index + current index

B Current index - popped index

C Stack top index - current index

D Current index - stack top index - 1

Width is current index minus new stack top index minus one.

What is the overall time complexity of this stack-based algorithm?

A O(n log n)

B O(n)

C O(n^2)

D O(log n)

Each bar is pushed and popped once, so time complexity is O(n).

Explain step-by-step how the stack helps find the largest rectangle in a histogram.

Think about how the stack keeps track of bars and when you calculate areas.

Describe how to calculate the width of the rectangle when popping a bar from the stack.

Width depends on the distance between bars around the popped bar.

Practice

1. What is the main purpose of using a stack in the Largest Rectangle in Histogram problem?

easy

A. To reverse the order of bars for easier calculation

B. To store the heights of all bars in sorted order

C. To keep track of bars' indices with increasing heights

D. To count the total number of bars in the histogram

Solution

1. Step 1: Understand the role of the stack

   The stack is used to store indices of bars in increasing height order to efficiently find the largest rectangle.

2. Step 2: Explain why increasing order is important

   When a bar with smaller height appears, we pop from the stack to calculate areas with bars taller than the current one.

3. Final Answer:

   To keep track of bars' indices with increasing heights -> Option C

4. Quick Check:

   Stack stores indices in increasing height order [OK]

Hint: Stack stores indices of increasing height bars [OK]

Common Mistakes:

• Thinking stack stores heights instead of indices
• Assuming stack sorts bars by height
• Using stack to count bars instead of track indices

2. Which of the following Python code snippets correctly initializes an empty stack for the Largest Rectangle in Histogram algorithm?

easy

A. stack = ()

B. stack = {}

C. stack = None

D. stack = []

Solution

1. Step 1: Identify correct data structure for stack

   In Python, a list is commonly used as a stack because it supports append() and pop() operations.

2. Step 2: Check each option

   stack = [] uses a list ([]), which is correct. stack = {} uses a dictionary ({}), not suitable. stack = None assigns None, not a stack. stack = () uses a tuple (()), which is immutable.

3. Final Answer:

   stack = [] -> Option D

4. Quick Check:

   List [] is correct stack initialization [OK]

Hint: Use list [] for stack in Python [OK]

Common Mistakes:

• Using dictionary {} instead of list
• Using tuple () which is immutable
• Assigning None instead of a list

3. What is the output of the following code snippet for the histogram heights = [2, 1, 5, 6, 2, 3]?

def largest_rectangle_area(heights):
    stack = []
    max_area = 0
    for i, h in enumerate(heights + [0]):
        while stack and heights[stack[-1]] > h:
            height = heights[stack.pop()]
            width = i if not stack else i - stack[-1] - 1
            max_area = max(max_area, height * width)
        stack.append(i)
    return max_area

print(largest_rectangle_area([2, 1, 5, 6, 2, 3]))

medium

A. 10

B. 12

C. 8

D. 6

Solution

1. Step 1: Trace the stack and area calculation

   Iterate through heights with an extra 0 at the end to pop all bars. The largest rectangle area found is 10 (from bars with heights 5 and 6).

2. Step 2: Confirm max area calculation

   The max area is calculated as max(10, others), so final answer is 10.

3. Final Answer:

   10 -> Option A

4. Quick Check:

   Largest rectangle area = 10 [OK]

Hint: Add zero height at end to pop all bars [OK]

Common Mistakes:

• Forgetting to add zero at end of heights
• Incorrect width calculation
• Not popping all bars from stack

4. Find the error in this code snippet for Largest Rectangle in Histogram:

def largest_rectangle_area(heights):
    stack = []
    max_area = 0
    for i, h in enumerate(heights + [0]):
        while stack and heights[stack[-1]] >= h:
            height = heights[stack.pop()]
            width = i - stack[-1] - 1
            max_area = max(max_area, height * width)
        stack.append(i)
    return max_area

print(largest_rectangle_area([2, 1, 5, 6, 2, 3]))

medium

A. Width calculation should be i - stack[-1] - 1

B. Missing adding zero height at end of heights

C. Comparison should be > instead of >=

D. Stack should store heights, not indices

Solution

1. Step 1: Identify width calculation mistake

   Width is calculated as i - stack[-1], but it should be i - stack[-1] - 1 to exclude the popped bar's index.

2. Step 2: Confirm other parts

   Adding zero at end is optional but common; comparison >= is acceptable; stack stores indices correctly.

3. Final Answer:

   Width calculation should be i - stack[-1] - 1 -> Option A

4. Quick Check:

   Width = i - stack[-1] - 1 [OK]

Hint: Width = current index - previous stack top - 1 [OK]

Common Mistakes:

• Incorrect width calculation causing wrong area
• Forgetting to add zero at end (optional)
• Confusing stack contents (indices vs heights)

5. Given the histogram heights = [6, 2, 5, 4, 5, 1, 6], what is the largest rectangle area using the stack approach?

hard

A. 10

B. 15

C. 12

D. 8

Solution

1. Step 1: Use stack to find largest rectangle

   Traverse bars with an extra 0 at end. The largest rectangle is formed by heights 5, 4, 5 spanning width 3, area = 12, but a larger rectangle is formed by heights 6 spanning width 2, area = 12, and also by heights 6 spanning width 1, area = 6. However, the maximum area is 15 formed by heights 5, 4, 5, 1, 6 combined correctly.

2. Step 2: Confirm no larger area exists

   After careful calculation, the largest rectangle area is 15 (from bars at indices 2 to 4 with height 5).

3. Final Answer:

   15 -> Option B

4. Quick Check:

   Max area = 15 from bars 5,4,5 [OK]

Hint: Check rectangles formed by popped bars for max area [OK]

Common Mistakes:

• Ignoring width when calculating area
• Not adding zero height at end to pop all bars
• Miscomputing width boundaries