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Table Of Contents
easy
13. Roman to Integer
14. Longest Common Prefix
20. Valid Parentheses
26. Remove Duplicates from Sorted Array
35. Search Insert Position
69. Sqrt(x)
70. Climbing Stairs
88. Merge Sorted Array (In-Place)
104. Maximum Depth of Binary Tree
118. Pascal's Triangle
121. Best Time to Buy and Sell Stock
205. Isomorphic Strings
242. Valid Anagram
283. Move Zeroes
345. Reverse Vowels of a String
605. Can Place Flowers
704. Binary Search
796. Rotate String
1071. Greatest Common Divisor of Strings
1299. Replace Elements with Greatest Element on Right Side
1431. Kids With the Greatest Number of Candies
1614. Maximum Nesting Depth of the Parentheses
1752. Check if Array Is Sorted and Rotated
1768. Merge Strings Alternately
1903. Largest Odd Number in String
2965. Find Missing and Repeated Values
hard
25. Reverse Nodes in k-Group
26. Remove Duplicates from Sorted Array
27. Remove Element
42. Trapping Rain Water
51. N-Queens
55. Jump Game
80. Remove Duplicates from Sorted Array II
88. Merge Sorted Array
121. Best Time to Buy and Sell Stock
122. Best Time to Buy and Sell Stock II
189. Rotate Array
274. H-Index
medium
2. Add Two Numbers
3. Longest Substring Without Repeating Characters
5. Longest Palindromic Substring
8. String to Integer (atoi)
11. Container With Most Water
15. 3Sum
17. Letter Combinations of a Phone Number
19. Remove Nth Node From End of List
22. Generate Parentheses
33. Search in Rotated Sorted Array
34. Find First and Last Position of Element in Sorted Array
48. Rotate Image
49. Group Anagrams
50. Pow(x, n)
53. Maximum Subarray
54. Spiral Matrix
56. Merge Intervals
61. Rotate List
73. Set Matrix Zeroes
74. Search a 2D Matrix
75. Sort Colors
78. Subsets
137. Single Number II
138. Copy List with Random Pointer
150. Evaluate Reverse Polish Notation
151. Reverse Words in a String
153. Find Minimum in Rotated Sorted Array
155. Min Stack
162. Find Peak Element
169. Majority Element
198. House Robber
207. Course Schedule
215. Kth Largest Element in an Array
227. Basic Calculator II
236. Lowest Common Ancestor of a Binary Tree
237. Delete Node in a Linked List
238. Product of Array Except Self
451. Sort Characters By Frequency
540. Single Element in a Sorted Array
560. Subarray Sum Equals K
636. Exclusive Time of Functions
875. Koko Eating Bananas
1011. Capacity To Ship Packages Within D Days
1101. The Earliest Moment When Everyone Become Friends
1283. Find the Smallest Divisor Given a Threshold
2140. Solving Questions With Brainpower
3169. Count Days Without Meetings
3481. Apply Substitutions
rotate-array-approach-1
189. Rotate Array (Approach 2 )
189. Rotate Array (Approach 1 )
number-of-islands-approach-1
200. Number of Islands (Approach 2)
200. Number of Islands (Approach 1)
meeting-rooms-ii-approach-1
253. Approach Using Priority Queue
253. Meeting Rooms II
misc
Calculate Floor & Ceiling
Find Nth Root Of M
Flatten A Linked List
Implement Lower Bound
Implement Upper Bound
Number of occurrence
take-u-forward
Recently Solved
arrays
The Ultimate Array Pattern Playbook
faqs-hard
Count Inversions in an Array
Find The Repeating And Missing Number
Majority Element II
Maximum Product Subarray
Merge Sorted Array (In-Place)
Reverse Pairs
faqs-medium
3. 3Sum
4. 4Sum
Maximum Subarray
Leaders in an Array
Majority Element
Next Permutation
Get specific element from Pascal's Triangle
Pascal's Triangle II (Row Generation)
Generate Pascal's Triangle (Full)
Spiral Matrix Traversal
Rearrange Array Elements by Sign
Rotate Image
Sort Colors (Dutch National Flag)
Two Sum
fundamentals
Check if Array is Sorted
Largest Element in an Array
Array Rotation (Left and Right)
Left Rotate Array by One
Linear Search
Max Consecutive Ones
Second Largest Element in an Array
Single Number
logic-building
Missing Number
Intersection of Two Sorted Arrays (with Duplicates)
Move Zeros to End
Remove Duplicates from Sorted Array
Union of Two Sorted Arrays
binary-search
About
d-arrays
Find Row With Maximum 1'S
Search In A 2D Matrix
faqs
Aggressive Cows
Allocate Books
Find Peak Element
Kth Element Of 2 Sorted Arrays
Minimise Max Distance to Gas Stations
Split Array - Largest Sum
fundamentals
Lower Bound
Binary Search
Upper Bound
logic-building
Count Occurrences in a Sorted Array
Find Minimum in Rotated Sorted Array
Find out how many times the array is rotated
Find First and Last Position of Element in Sorted Array
Floor and Ceil in Sorted Array
Kth Missing Positive Number
Search in Rotated Sorted Array
Search in Rotated Sorted Array II (With Duplicates)
Search Insert Position
Single Element in a Sorted Array
on-answers
Capacity To Ship Packages Within D Days
Find Nth Root of M
Find Square Root of a Number
Smallest Divisor Given a Threshold
Koko Eating Bananas (Minimum Rate)
Minimum Days to Make M Bouquets
Painter's Partition Problem
Split Array Largest Sum
hashing
Theory
faqs
Subarray Sum Equals K
Count Subarrays with Given XOR K
Largest Subarray with 0 Sum
Longest Consecutive Sequence
Longest Subarray with Sum K
recursion
faqs-medium
Combination Sum II (Unique Combinations)
Combination Sum (Unbounded)
Subset Sums
hard
Letter Combinations of a Phone Number
implementation-problems
Generate Parentheses
Power Function: pow(x, n)
Subsets (The Power Set)
subsequence-pattern-problems
Subsequence Sum Existence
Count All Subsequences With Sum K
sorting
Bubble Sort
Insertion Sort
Merge Sort
Quick Sort
Selection Sort
string
Isomorphic Strings
Largest Odd Number in String
Longest Common Prefix
Reverse Words in a String
Code Scratch›take u forward›arrays›logic building

Remove Duplicates from Sorted Array

# Question

Given an array nums sorted in non-decreasing order, remove duplicates in-place such that each unique element appears only once. The relative order of elements should be kept. Return the number of unique elements kkk. The first kkk elements of nums should hold the unique values.

# Solution

# Pattern

Two-Pointer (Slow/Fast) One pointer tracks the "last unique" position, while the other "explores" the array for new values.

# How to Identify

  • Sorted Input: Essential because duplicates are guaranteed to be adjacent.
  • In-place Constraint: You cannot use a HashSet or an auxiliary array.
  • Ordered Result: The unique values must maintain their original sequence.

# Description

Step-by-step explanation:

  • Initialization: Start pointer i=0i = 0i=0. This represents the index of the first unique element.
  • Iteration: Use a second pointer jjj starting from 111 to the end of the array.
  • Comparison: Compare nums[i] (last unique) with nums[j] (current explorer).
  • Action: If nums[i] != nums[j], it means we found a new unique element. Increment iii and copy nums[j] to nums[i].
  • Completion: The total count of unique elements is i+1i + 1i+1.

# The Intuition

Think of this as "The Filter and Compact" method.

Imagine you are a librarian organizing a shelf of books that are already sorted by title, but some are duplicates. You keep your left hand on the last "unique" book you want to keep. Your right hand scans to the right. Every time your right hand finds a book with a different title, you move your left hand one spot to the right and put that new book there. You don't care about the extra books left on the right side of the shelf.

# Complexity

LabelWorstAverage
Time ComplexityO(n)O(n)O(n)O(n)O(n)O(n)
Space ComplexityO(1)O(1)O(1)O(1)O(1)O(1)

# Time Complexity

O(n)O(n)O(n) where nnn is the length of the array. Every element is visited exactly once by the fast pointer.

# Space Complexity

O(1)O(1)O(1) auxiliary space is used as the modification happens within the existing array memory.

# Code

class Solution {
    public int removeDuplicates(int[] nums) {
        // Base case: empty arrays have 0 unique elements
        if (nums == null || nums.length == 0) return 0;
        
        // i: The index where the last unique element was placed
        int i = 0;
        
        // j: The fast pointer searching for the next unique element
        for (int j = 1; j < nums.length; j++) {
            // If we find a new value that differs from the last unique one
            if (nums[j] != nums[i]) {
                // Increment our placement index
                i++;
                // Move the new unique value to the front
                nums[i] = nums[j];
            }
        }
        
        // Return count, which is index + 1
        return i + 1;
    }
}

# Caveats

  • Sorted Assumption: If the input is not sorted, this O(n)O(n)O(n) logic fails. You would need to sort first (O(nlog⁡n)O(n \log n)O(nlogn)) or use O(n)O(n)O(n) space with a Set.
  • Input Modification: The original array is destroyed. If the original data is needed elsewhere, this "in-place" requirement must be re-evaluated.

# Concepts to Think About

  • Read vs Write: In scenarios where writes are expensive (e.g., certain types of Flash memory), adding a check if (i != j) before the assignment nums[i] = nums[j] can reduce unnecessary writes.
  • In-place Algorithms: Common in system-level programming where memory is a premium resource.
  • Monotonicity: The fact that the array is sorted allows us to solve this in linear time without look-aheads.

# Logical Follow-up

Question: What if you are allowed to keep at most two occurrences of each element? Solution: Change the comparison to nums[j] != nums[i-1]. This allows the first and second occurrence to be kept but skips the third.

Question: What if the array is not sorted? Solution: You cannot achieve O(1)O(1)O(1) space and O(n)O(n)O(n) time. You either sort first (O(nlog⁡n)O(n \log n)O(nlogn) time, O(1)O(1)O(1) space) or use a HashSet (O(n)O(n)O(n) time, O(n)O(n)O(n) space).

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CONTENTS
QuestionSolutionPatternHow to IdentifyDescriptionThe IntuitionComplexityCodeCaveatsConcepts to Think AboutLogical Follow-up