Data Structures and Algorithms Tutorial 21 of 486
Foundations 17/41
Fundamentals
- Conditional Statements in DSA
- For Loop
- While Loop
- Functions
- Classes and Objects in DSA
- Order of Growth
- Asymptotic Analysis
- Big-O Notation
- Theta Notation
- Big-Omega Notation
- Time Complexity
- Space Complexity
- Input and Output
Maths, Pattern & Recursion
- Recursion
- Analysis of Recursion
- Even or Odd
- Sum of Natural Numbers
- Closest Number
- Sum of Consecutive Numbers
- Solid Rectangle
- Floyd's Triangle
- Hollow Rectangle
- Print 1 to N
- Print N to 1
- Factorial
- GCD
- Power
- Pyramid
- Hollow Diamond
- Count Digits
- Prime Testing
- Armstrong Number
- Trailing Zeros
- Prime Factors
- All Divisors
- Butterfly Pattern
- Palindrome Number
- Tower of Hanoi
- Non-Attacking Knights
- Josephus Problem
- Water Jug Problem
Core Data Structures 0/224
Array & String
- Array Basics
- String Basics
- Matrix Basics
- Is Sorted
- Multiply with Adjacent
- Reverse Array
- Reverse in Groups
- Rotate Array
- Generate All Subarrays
- Arrange by Sign
- Stock Buy/Sell - One Transaction
- Stock Buy/Sell - Multiple Transactions
- Leaders in Array
- Same Strings
- Palindrome String
- Toggle Case
- Remove Occurrences
- Remove Spaces
- Check Subsequence
- First Non-Repeating Character
- Pangram
- Majority Element
- Majority Element II
- Sorted Subsequence of 3
- Count Strictly Increasing Subarrays
- Next Permutation
- Kadane's Algorithm
- Sum of All Subarrays
- Maximum Product Subarray
- Implement atoi
- URLify
- Multiply Large Numbers
- Diagonal Traversal
- Magic Square
- Boundary Traversal
- Spiral Matrix
- Toeplitz Matrix
- Matrix Zig-Zag
- Transpose of Matrix
- Rotate Matrix by 90 Degrees
- Conway's Game of Life
- Queries in a Matrix
- Set Matrix Zeroes
- Maximum Circular Subarray Sum
- Next Smallest Palindrome
- Lexicographic Rank
- Text Justification
Linked List
- Linked List Basics
- Singly Linked List
- Doubly Linked List
- Circular Linked List
- Reverse Singly Linked List
- Reverse Doubly Linked List
- Reverse in Groups
- Reorder List
- Find Middle
- Remove Nth From End
- Check Palindrome
- Detect Cycle
- Intersection of Y-Shaped Lists
- Sort 0s 1s 2s
- Add Two Numbers
- Merge K Sorted Lists
- Browser History
- Twitter Design
- LRU Cache
- LFU Cache
- Flatten Linked List
- Clone Linked List With Random Pointer
Stack
- Stack Basics
- Reverse Stack
- Sort Stack
- Balanced Parentheses
- Postfix Evaluation
- Infix Evaluation
- Infix to Postfix
- Redundant Brackets
- Longest Valid Parentheses
- Stack Using Queues
- Two Stacks in an Array
- K Stacks in an Array
- Stack With getMin
- Remove K Digits
- Next Greater Element
- Stock Span Problem
- Previous Smaller Element
- Largest Rectangle in Histogram
- Trapping Rain Water
- Decode String
Queue
- Queue Basics
- Circular Queue
- Queue Using Stacks
- FIFO Page Replacement
- Reverse a Queue
- Reverse First K Elements
- Interleave Queue
- K Queues in an Array
- First Non-Repeating Character in a Stream
- Minimum Knight Steps
Deque
- Deque Basics
- Circular Array Implementation
- Lexicographically Largest Permutation
- Generate Bitonic Sequence
- Sliding Window Maximum
- Longest Subarray With Difference <= X
- Minimum Deques to Sort Array
Hashing
- Hashing Basics
- Linear Probing
- Separate Chaining
- Quadratic Probing
- Distinct in Array
- Is Subset
- Union of Arrays
- Intersection of Arrays
- Two Sum
- Fizz Buzz
- Pair Sums Divisible by K
- Roman to Integer
- Isomorphic Strings
- Count Frequencies
- Most Frequent Element
- Maximum Subsets
- Anagrams
- Longest Consecutive Subsequence
- Consecutive Subsequence
Heap
- Heap Basics
- Check for Heap
- Heap Sort
- Kth Largest
- K Largest Elements
- Height of Heap
- Connect N Ropes
- Nearly Sorted Array
- BST to Min Heap
- K Max Sum Combinations
- Median in a Stream
- Kth Largest in a Stream
- Merge K Sorted Arrays/Lists
- Range Covering K Sorted Lists
- Skyline Problem
- Sort by Frequency
Binary Tree
- Binary Tree Basics
- Inorder Traversal
- Preorder Traversal
- Postorder Traversal
- Level Order Traversal
- Size of Tree
- Depth of Tree
- Maximum Width
- Check Balanced Tree
- Identical Trees
- Mirror Tree
- Sum Tree
- Left View
- Right View
- Path Sum
- Maximum Path Sum
- Serialize and Deserialize
- Iterative Inorder
- Iterative Preorder
- Iterative Postorder
- Morris Inorder
- Diameter of Tree
- Boundary Traversal
- Tree From Preorder and Inorder
- Connect Nodes at Same Level
- Invert Tree
- Flatten Tree
- Vertical Traversal
- Bottom View
- Top View
- Spiral Level Order
- Lowest Common Ancestor
- Distance K
- Subtree Check
Binary Search Tree
- BST Basics
- Search in BST
- Insert in BST
- Delete in BST
- Ceil in BST
- Floor in BST
- Predecessor and Successor
- Kth Smallest Element
- Two Sum in BST
- Sorted Array to BST
- Merge Two BSTs
- Validate BST
- Lowest Common Ancestor
- Recover BST
- Largest BST Subtree
Trie
- Implement Trie
- Longest Word With All Prefixes
- Count Distinct Substrings
- Maximum XOR of Two Numbers
- Maximum XOR Queries
- Pairs With XOR Less Than K
- Search Suggestions System
- Palindrome Pairs
Graph
- Graph Representation
- BFS Traversal
- DFS Traversal
- Flood Fill
- Number of Islands
- Connected Components in Undirected Graph
- Cycle in Undirected Graph
- Cycle in Directed Graph
- Bipartite Graph
- Rotten Oranges
- Topological Sort
- Course Schedule I
- Course Schedule II
- Alien Dictionary
- Dijkstra's Algorithm
- Floyd Warshall
- Bellman-Ford
- Minimum Cost Path
- Shortest Cycle in Undirected Graph
- Distance of Nearest 1
- Word Ladder
- Prim's Algorithm
- Disjoint Set Union
- Kruskal's Algorithm
- Detect Cycle Using DSU
- Number of Connected Components
Problem-Solving Patterns 0/99
Two-Pointer
- Two-Pointer Technique
- Two Sum in Sorted Array
- Smallest Subarray
- Unique Elements
- Sentence Palindrome
- Three Sum
- Celebrity Problem
- Closest Pair from Two Arrays
- Container With Most Water
- Common Elements in Three Arrays
- Reverse Words
- Four Sum
- Closest Triplet
- Count Triplets
Sliding Window
- Sliding Window Technique
- Maximum Sum Subarray of Size K
- Maximum XOR of K Size
- Distinct in Every Window
- MEX of Subarrays
- Minimum Swaps to Group All 1s
- First Negative in Every Window
- Chocolate Distribution
- Maximize Ones
- Equal Substring With Cost <= K
- Fruit Into Baskets
- Subarray With Given Sum
- Smallest Subarray With Sum Greater Than X
- Minimum Window Subsequence
- Minimum Window Substring
- Subarrays With K Odds
- Subarrays Less Than K
- Longest Substring With Distinct Characters
- Longest Substring With K Unique Characters
- Count Anagrams
Prefix Sum
- Prefix Sum Basics
- Prefix Sum Array
- 2D Prefix Sum
- Range Queries
- Equilibrium Index
- Product of Array Except Self
- Difference Array
- 2D Difference Array
- Subarray With Zero Sum
- Largest Subarray With Zero Sum
- Largest Subarray With Equal 0s and 1s
- Longest Subarray With Sum K
- Count Subarrays With Sum K
- Count Subarrays With Given XOR
Bit Manipulation
- Bit Manipulation Basics
- Swap Without Third Variable
- Kth Set Bit
- Only Set Bit
- Power of Two
- Sort by Set Bits
- Power of Four
- Binary Palindrome
- Rotate Bits
- Swap Odd and Even Bits
- Count Set Bits
- Count Total Set Bits
- Maximum Consecutive 1s
- Missing Number
- One Odd Occurring
- Two Odd Occurring
- Missing and Repeating
- Unique Numbers II
- Gray Codes
- Hamming Distance
- Sum of Pair XORs
- Sum of Subset XORs
- Subarray XORs
- Subsets
- Subsequences
Backtracking
- Backtracking Basics
- Permutations
- Rat in a Maze
- Word Search
- N-Queen Problem
- Sudoku Solver
- Word Break
- Knight's Tour
- Palindromic Partitions
- M-Coloring
Greedy
- Greedy Algorithm Basics
- Fractional Knapsack
- Assign Cookies
- Smallest Subset With Greater Sum
- Minimum Notes With Given Sum
- Activity Selection
- Huffman Coding
- Jump Game
- Job Sequencing
- Non-Overlapping Intervals
- Gas Station
- Stable Marriage
- Minimize Maximum Height Difference
- No Two Adjacent Same
- Minimize Cash Flow
- Min Time to Finish Jobs With Constraints
Core Algorithms 0/122
Searching
- Searching Basics
- Largest Element
- Second Largest
- Local Min and Max
- Search Insert Position
- Lower Bound
- Upper Bound
- Single Element in Sorted Array
- Missing Natural Number
- Count Occurrences
- Search in 2D Matrix
- Search in Sorted and Rotated Array
- Search in Sorted and Rotated Array II
- K Closest Elements
- Search in Almost Sorted Array
- Peak Element
- Peak Element in 2D
- Range Based Counts
- Kth Missing Positive
- Search in Row-Column Sorted Matrix
- Square Root
- Nth Root
- Check Power
- Book Allocation
- Koko Eating Bananas
- Aggressive Cows
- Median in Row Sorted Matrix
- Kth Smallest in Row and Column Sorted Matrix
- M Bouquets
- Kth in Multiplication Table
- Median of Two Sorted Arrays
- Kth Element of Two Sorted Arrays
Sorting
- Sorting Basics
- Wave Form
- Sort by Length
- Minimum Difference Pair
- Merge Overlapping Intervals
- Form Largest Number
- Meeting Rooms
- Insert and Merge Intervals
- Minimize Moves
- Quick Sort
- Sort Binary Array
- Move Zeroes to End
- Sort Ternary Array
- Merge Sort
- Union of Two Sorted Arrays
- Intersection of Two Sorted Arrays
- Merge Without Extra Space
- Minimum Platforms
- Inversion Count
- Cycle Sort
- Minimum Missing Positive
- Minimum Swaps to Sort
Dynamic Programming
- Dynamic Programming Basics
- Climbing Stairs
- Count Without Consecutive 1s
- Frog Jump
- House Robber
- Maximum Segments
- Coin Change
- Decode Ways
- Word Break
- Unique Paths
- Minimum Cost Path
- Longest Common Subsequence
- Edit Distance
- Distinct Subsequences
- Largest Square Submatrix of 1s
- Partition Equal Subset Sum
- Subset Sum
- Count Subsets With Given Sum
- Target Sum
- 0/1 Knapsack
- Coin Change II
- Rod Cutting
- Unique Paths in a Grid
- Maximum Path Sum in Matrix
- Longest Increasing Path
- Longest Common Substring
- Shortest Common Supersequence
- Interleaving String
- Wildcard Matching
- Longest Palindromic Substring
- Buy/Sell With Cooldown
- Buy/Sell With At Most Two Transactions
- Buy/Sell With K Transactions
- Buy/Sell With Transaction Fee
- Longest Increasing Subsequence
- Number of LIS
- Longest Bitonic Subsequence
- Longest String Chain
- Matrix Chain Multiplication
- Minimum Cost to Cut a Stick
- Palindrome Partitioning
- Boolean Parenthesization
- Partition Array for Maximum Sum
- Egg Dropping
String Matching
- Substring Search
- Rabin-Karp
- KMP Algorithm
- Z Algorithm
- Longest Prefix Suffix
- Manacher's Algorithm
- Longest Palindromic Substring
- Palindrome Substring Queries
- Minimum Repeats for Substring
Number Theory
- nCr
- Euler's Totient
- Sieve of Eratosthenes
- Pascal's Triangle
- Modular Exponentiation
- Segmented Sieve
Range Query
- Segment Tree
- Min-Max Range Queries
- Range LCM Queries
- Range XOR Queries
- Lazy Propagation
- Flipping Sign
- Segment Tree on N-ary Rooted Tree
- Fenwick Tree
- Sum and Update Queries on 3D Matrix
Floyd's Triangle
Learn how to generate Floyd's Triangle using nested loops and understand the row-by-row numbering pattern.
On this page
Floyd's Triangle
Floyd's Triangle is a number pattern where consecutive integers are printed in rows, with each new row containing one more number than the previous row.
For 5 rows:
1
2 3
4 5 6
7 8 9 10
11 12 13 14 15
It is a useful pattern problem for understanding nested loops, row structure, and maintaining a running value.
Pattern Logic
For each row:
- Row 1 contains
1number. - Row 2 contains
2numbers. - Row 3 contains
3numbers. - Row
NcontainsNnumbers.
The numbers continue increasing across rows.
For example:
Row 1 → 1
Row 2 → 2 3
Row 3 → 4 5 6
The next number after one row becomes the starting number of the next row.
C Program
#include <stdio.h>
int main() {
int rows = 5;
int num = 1;
for (int i = 1; i <= rows; i++) {
for (int j = 1; j <= i; j++) {
printf("%d ", num);
num++;
}
printf("\n");
}
return 0;
}
Output:
1
2 3
4 5 6
7 8 9 10
11 12 13 14 15
How It Works
The outer loop controls the number of rows:
for (int i = 1; i <= rows; i++)
The inner loop prints i numbers in the current row:
for (int j = 1; j <= i; j++)
The variable num keeps track of the next number to print:
printf("%d ", num);
num++;
Therefore, the number continues increasing even after moving to the next row.
Algorithm
- Set
num = 1. - Start from the first row.
- Print as many numbers as the current row number.
- Increase
numafter every number. - Move to the next row.
- Repeat until all rows are printed.
Pseudocode
num = 1
FOR i = 1 TO rows
FOR j = 1 TO i
PRINT num
num = num + 1
PRINT new line
Complexity
For N rows, the total number of numbers printed is:
1 + 2 + 3 + ... + N
which is:
N(N + 1) / 2
Therefore:
Time Complexity: O(N²)
Space Complexity: O(1)
The O(N²) time is because the program prints approximately N² / 2 numbers.
Common Mistakes
- Resetting
numinside the outer loop. - Using
j <= rowsinstead ofj <= i. - Forgetting to increment
num. - Forgetting the newline after each row.
For example, num should be initialized before the outer loop:
int num = 1;
for (...) {
...
}
not inside each row.
Quick Reference
int num = 1;
for (int i = 1; i <= rows; i++) {
for (int j = 1; j <= i; j++) {
printf("%d ", num++);
}
printf("\n");
}
The key pattern is:
Row 1 → 1 number
Row 2 → 2 numbers
Row 3 → 3 numbers
...
Row N → N numbers
Key Takeaways
- Floyd's Triangle contains consecutive numbers arranged in rows.
- Row
icontains exactlyinumbers. - Nested loops are used to generate the pattern.
- A running variable keeps the numbers consecutive across rows.
- Printing
Nrows requiresO(N²)time.
Practice Questions
- Print Floyd's Triangle for
Nrows. - Start Floyd's Triangle from a number other than
1. - Print Floyd's Triangle in reverse order.
- Print only the odd numbers in a triangular pattern.
- Modify the pattern to print consecutive even numbers.
What's Next?
Next, practice another number pattern to strengthen your understanding of nested loops and row-column relationships.
Related
-
Solid Rectangle
Learn how to print a solid rectangle pattern using nested loops and understand the row-column logic behind pattern problems.
-
Hollow Rectangle
Learn how to print a hollow rectangle pattern by printing characters only on its boundary using nested loops and conditions.
-
Sum of Natural Numbers
Learn how to calculate the sum of the first N natural numbers using iteration and the mathematical formula.
-
Sum of Consecutive Numbers
Learn how to calculate the sum of consecutive numbers using a loop and a mathematical formula, with complexity and examples.