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DSA Visualizations /

Overview of TechniquesOverview of Techniques14
❯

  1. 1Overview of DSA Problem Solving Techniques
  2. 2Brute Force Technique in DSA
  3. 3Greedy Algorithm Technique in DSA
  4. 4Divide and Conquer Technique in DSA
  5. 5Dynamic Programming Technique in DSA
  6. 6Backtracking Technique in DSA
  7. 7Recursion Technique in DSA
  8. 8Sliding Window Technique in DSA
  9. 9Two Pointers Technique
  10. 10Binary Search Technique
  11. 11Tree / Graph Traversal Technique in DSA
  12. 12Bit Manipulation Technique in DSA
  13. 13Hashing Technique
  14. 14Heaps Technique in DSA

SortingSorting10
❯

  1. 1Bubble Sort
  2. 2Selection Sort
  3. 3Insertion Sort
  4. 4Merge Sort
  5. 5Quick Sort
  6. 6Heap Sort
  7. 7Radix Sort
  8. 8Counting Sort
  9. 9Bucket Sort
  10. 10Shell Sort

ArraysArrays32
❯

  1. 1Find Maximum and Minimum in Array using Loop
  2. 2Find Second Largest in Array
  3. 3Find Second Smallest in Array
  4. 4Reverse Array using Two Pointers
  5. 5Check if Array is Sorted
  6. 6Remove Duplicates from Sorted Array
  7. 7Left Rotate an Array by One Place
  8. 8Left Rotate an Array by K Places
  9. 9Move Zeroes in Array to End
  10. 10Linear Search in Array
  11. 11Union of Two Arrays
  12. 12Find Missing Number in Array
  13. 13Max Consecutive Ones in Array
  14. 14Find Kth Smallest Element
  15. 15Longest Subarray with Given Sum (Positives)
  16. 16Longest Subarray with Given Sum (Positives and Negatives)
  17. 17Find Majority Element in Array (more than n/2 times)
  18. 18Find Majority Element in Array (more than n/3 times)
  19. 19Maximum Subarray Sum using Kadane's Algorithm
  20. 20Print Subarray with Maximum Sum
  21. 21Stock Buy and Sell
  22. 22Rearrange Array Alternating Positive and Negative Elements
  23. 23Next Permutation of Array
  24. 24Leaders in an Array
  25. 25Longest Consecutive Sequence in Array
  26. 26Count Subarrays with Given Sum
  27. 27Sort an Array of 0s, 1s, and 2s
  28. 28Two Sum Problem
  29. 29Three Sum Problem
  30. 304 Sum Problem
  31. 31Find Length of Largest Subarray with 0 Sum
  32. 32Find Maximum Product Subarray

Arrays - Binary SearchArrays - Binary Search28
❯

  1. 1Binary Search in Array using Iteration
  2. 2Find Lower Bound in Sorted Array
  3. 3Find Upper Bound in Sorted Array
  4. 4Search Insert Position in Sorted Array (Lower Bound Approach)
  5. 5Floor and Ceil in Sorted Array
  6. 6First Occurrence in a Sorted Array
  7. 7Last Occurrence in a Sorted Array
  8. 8Count Occurrences in Sorted Array
  9. 9Search Element in a Rotated Sorted Array
  10. 10Search in Rotated Sorted Array with Duplicates
  11. 11Minimum in Rotated Sorted Array
  12. 12Find Rotation Count in Sorted Array
  13. 13Search Single Element in Sorted Array
  14. 14Find Peak Element in Array
  15. 15Square Root using Binary Search
  16. 16Nth Root of a Number using Binary Search
  17. 17Koko Eating Bananas
  18. 18Minimum Days to Make M Bouquets
  19. 19Find the Smallest Divisor Given a Threshold
  20. 20Capacity to Ship Packages within D Days
  21. 21Kth Missing Positive Number
  22. 22Aggressive Cows Problem
  23. 23Allocate Minimum Number of Pages
  24. 24Split Array - Minimize Largest Sum
  25. 25Painter's Partition Problem
  26. 26Minimize Maximum Distance Between Gas Stations
  27. 27Median of Two Sorted Arrays of Different Sizes
  28. 28K-th Element of Two Sorted Arrays

StringsStrings18
❯

  1. 1Reverse Words in a String
  2. 2Find the Largest Odd Number in a Numeric String
  3. 3Find Longest Common Prefix in Array of Strings
  4. 4Check If Two Strings Are Isomorphic - Optimal HashMap Solution
  5. 5Check String Rotation using Concatenation - Optimal Approach
  6. 6Check if Two Strings Are Anagrams - Optimal Approach
  7. 7Sort Characters by Frequency - Optimal HashMap and Heap Approach
  8. 8Find Longest Palindromic Substring - Dynamic Programming Approach
  9. 9Find Longest Palindromic Substring Without Dynamic Programming
  10. 10Remove Outermost Parentheses in String
  11. 11Find Maximum Nesting Depth of Parentheses - Optimal Stack-Free Solution
  12. 12Convert Roman Numerals to Integer - Efficient Approach
  13. 13Convert Integer to Roman Numeral - Step-by-Step for Beginners
  14. 14Implement Atoi - Convert String to Integer in Java
  15. 15Count Number of Substrings in a String - Explanation with Formula
  16. 16Edit Distance Problem
  17. 17Calculate Sum of Beauty of All Substrings - Optimal Approach
  18. 18Reverse Each Word in a String - Optimal Approach

MatrixMatrix3
❯

  1. 1Set Matrix Zeroes
  2. 2Rotate Matrix by 90 Degrees Clockwise
  3. 3Print Matrix in Spiral Manner

Matrix - Binary SearchMatrix - Binary Search5
❯

  1. 1Row with Maximum Number of 1's
  2. 2Search in a Sorted 2D Matrix
  3. 3Search in Row and Column-wise Sorted Matrix
  4. 4Find Target in 2D Matrix
  5. 5Matrix Median

Binary TreesBinary Trees36
❯

  1. 1Preorder Traversal of a Binary Tree using Recursion
  2. 2Preorder Traversal of a Binary Tree using Iteration
  3. 3Postorder Traversal of a Binary Tree Using Recursion
  4. 4Postorder Traversal of a Binary Tree using Iteration
  5. 5Level Order Traversal of a Binary Tree using Recursion
  6. 6Level Order Traversal of a Binary Tree using Iteration
  7. 7Reverse Level Order Traversal of a Binary Tree using Iteration
  8. 8Reverse Level Order Traversal of a Binary Tree using Recursion
  9. 9Find Height of a Binary Tree
  10. 10Find Diameter of a Binary Tree
  11. 11Find Mirror of a Binary Tree - Todo
  12. 12Inorder Traversal of a Binary Tree using Recursion
  13. 13Inorder Traversal of a Binary Tree using Iteration
  14. 14Left View of a Binary Tree
  15. 15Right View of a Binary Tree
  16. 16Top View of a Binary Tree
  17. 17Bottom View of a Binary Tree
  18. 18Zigzag Traversal of a Binary Tree
  19. 19Check if a Binary Tree is Balanced
  20. 20Diagonal Traversal of a Binary Tree
  21. 21Boundary Traversal of a Binary Tree
  22. 22Construct a Binary Tree from a String with Bracket Representation
  23. 23Convert a Binary Tree into a Doubly Linked List
  24. 24Convert a Binary Tree into a Sum Tree
  25. 25Find Minimum Swaps Required to Convert a Binary Tree into a BST
  26. 26Check if a Binary Tree is a Sum Tree
  27. 27Check if All Leaf Nodes are at the Same Level in a Binary Tree
  28. 28Lowest Common Ancestor (LCA) in a Binary Tree
  29. 29Solve the Tree Isomorphism Problem
  30. 30Check if a Binary Tree Contains Duplicate Subtrees of Size 2 or More
  31. 31Check if Two Binary Trees are Mirror Images
  32. 32Calculate the Sum of Nodes on the Longest Path from Root to Leaf in a Binary Tree
  33. 33Print All Paths in a Binary Tree with a Given Sum
  34. 34Find the Distance Between Two Nodes in a Binary Tree
  35. 35Find the kth Ancestor of a Node in a Binary Tree
  36. 36Find All Duplicate Subtrees in a Binary Tree

Binary Search TreesBinary Search Trees14
❯

  1. 1Find a Value in a Binary Search Tree
  2. 2Delete a Node in a Binary Search Tree
  3. 3Find the Minimum Value in a Binary Search Tree
  4. 4Find the Maximum Value in a Binary Search Tree
  5. 5Find the Inorder Successor in a Binary Search Tree
  6. 6Find the Inorder Predecessor in a Binary Search Tree
  7. 7Check if a Binary Tree is a Binary Search Tree
  8. 8Find the Lowest Common Ancestor of Two Nodes in a Binary Search Tree
  9. 9Convert a Binary Tree into a Binary Search Tree
  10. 10Balance a Binary Search Tree
  11. 11Merge Two Binary Search Trees
  12. 12Find the kth Largest Element in a Binary Search Tree
  13. 13Find the kth Smallest Element in a Binary Search Tree
  14. 14Flatten a Binary Search Tree into a Sorted List

Remove Duplicates from Sorted Array using Two Pointers - Optimal Algorithm

Topic Contents

ProblemExamplesSolutionVisualizationAlgorithmCodeTimeSpaceDetailed Example

Problem Statement

Given a sorted array of integers, your task is to remove the duplicate elements in-place such that each element appears only once. The relative order of the elements should be maintained.

Examples❯

Input ArrayReturned LengthModified Array (first k elements)Description
[1, 1, 2]2[1, 2]1 is repeated, only unique values retained
[0, 0, 1, 1, 1, 2, 2, 3, 3, 4]5[0, 1, 2, 3, 4]All duplicates removed, unique values in-place
[1, 2, 3, 4]4[1, 2, 3, 4]No duplicates, array remains the same
[1, 1, 1, 1]1[1]All elements are same, only one remains
[5]1[5]Single element, no duplicates to remove
[]0[]Empty array, result is also empty

Solution❯

Since the input array is already sorted, any duplicates will appear next to each other. This makes it possible to remove duplicates by comparing each element with the previous one and only keeping the first occurrence of each value.

How It Works

We use a two-pointer approach to solve this efficiently in-place. One pointer (let’s call it i) will keep track of the position of the last unique element found. The other pointer (j) will move forward through the array, scanning for new unique elements.

Every time we find that arr[j] != arr[i], it means we’ve found a new value that hasn’t been seen yet. So we increment i and copy arr[j] into arr[i]. This way, all the unique elements are gathered at the beginning of the array in order.

What About Edge Cases?

  • Empty Array: If the input array has no elements, then there are no values to process, and the result is simply 0.
  • Single Element: An array with one value is already unique. So we return 1, and the array remains unchanged.
  • All Duplicates: For arrays like [2, 2, 2, 2], we keep only one '2', so the final length is 1.
  • All Unique: In a case like [1, 2, 3, 4], no changes are needed, and we return the original length.

Why This is Efficient

This method runs in O(n) time because we scan the array once. It also uses O(1) space since we don’t use any extra data structures—just the input array and two pointers. This makes it an optimal solution.

At the end, the array is modified so that the first k elements contain the unique values, and you can ignore the rest.

Visualization

Algorithm Steps

  1. Given a sorted array arr.
  2. Use two pointers: i to track unique elements and j to iterate through the array.
  3. Start with i = 0 and j = 1.
  4. If arr[j] != arr[i], increment i and update arr[i] = arr[j].
  5. Continue this until j reaches the end of the array.
  6. The first i + 1 elements are the array with duplicates removed.

Code

Python
JavaScript
Java
C++
C
def remove_duplicates(arr):
    if not arr:
        return 0
    i = 0
    for j in range(1, len(arr)):
        if arr[j] != arr[i]:
            i += 1
            arr[i] = arr[j]
    return i + 1

# Sample Input
arr = [1, 1, 2, 2, 3, 4, 4]
k = remove_duplicates(arr)
print("After removing duplicates:", arr[:k])

Time Complexity

CaseTime ComplexityExplanation
Best CaseO(n)Even if all elements are duplicates, the algorithm still iterates through the entire array once.
Average CaseO(n)Regardless of how many duplicates exist, each element is visited once using the two-pointer approach.
Average CaseO(n)In the worst case where all elements are unique, the algorithm still makes a single pass through the array.

Space Complexity

O(1)

Explanation: The algorithm operates in-place and only uses two pointers to modify the array without allocating extra space.

Detailed Step by Step Example

Let's remove duplicates from the sorted array using the two-pointer technique.

{ "array": [1,1,2,2,3,4,4], "showIndices": true }

Initialize pointer i = 0 to track the last unique element. Start loop from j = 1.

Check index 1

Compare arr[1] = 1 with arr[0] = 1.

Duplicate found. Do nothing.

{ "array": [1,1,2,2,3,4,4], "showIndices": true, "highlightIndices": [0, 1], "labels": { "0": "i", "1": "j" } }

Check index 2

Compare arr[2] = 2 with arr[0] = 1.

Values are different. Increment i to 1 and set arr[1] = 2.

{ "array": [1,2,2,2,3,4,4], "showIndices": true, "highlightIndices": [1, 2], "labels": { "1": "i", "2": "j" } }

Check index 3

Compare arr[3] = 2 with arr[1] = 2.

Duplicate found. Do nothing.

{ "array": [1,2,2,2,3,4,4], "showIndices": true, "highlightIndices": [1, 3], "labels": { "1": "i", "3": "j" } }

Check index 4

Compare arr[4] = 3 with arr[1] = 2.

Values are different. Increment i to 2 and set arr[2] = 3.

{ "array": [1,2,3,2,3,4,4], "showIndices": true, "highlightIndices": [2, 4], "labels": { "2": "i", "4": "j" } }

Check index 5

Compare arr[5] = 4 with arr[2] = 3.

Values are different. Increment i to 3 and set arr[3] = 4.

{ "array": [1,2,3,4,3,4,4], "showIndices": true, "highlightIndices": [3, 5], "labels": { "3": "i", "5": "j" } }

Check index 6

Compare arr[6] = 4 with arr[3] = 4.

Duplicate found. Do nothing.

{ "array": [1,2,3,4,3,4,4], "showIndices": true, "highlightIndices": [3, 6], "labels": { "3": "i", "6": "j" } }

Final Result:

Array without duplicates (first i + 1 which is 4 elements): [1,2,3,4]

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