Data Structure & Algorithms
  • 🖌️Unlocking the Power of Algorithms with C#
  • Data Structure
    • Data Structure
    • Big O
    • Array
    • Linked Lists
    • Stacks
    • Queues
    • Hash Tables
    • Trees
    • Graphs
    • Heap Sort
    • ParkingLot Algorithm
    • LRU cache
    • Priority Queue
  • Algorithms
    • Algorithm
    • Recursion
    • Sorting
    • Searching
    • Dynamic Programming
  • Problems
    • Array
      • Two Sum
      • Two Sum II - Input Array Is Sorted
      • Contains Duplicate
      • Maximum Subarray
      • House Robber
      • Move Zeroes
      • Rotate Array
      • Plus One
      • Find number of subarrays with even length
      • Find number of subarrays with even sum
      • Find Missing Element
      • Reduce Array Size to The Half
      • Remove Duplicates
      • Merge Sorted Arrays
      • Arrays Intersection
      • 3Sum
      • Trapping Rain Water
      • Maximum sum of a subarray
      • Longest Subarray
      • Subarray Sum Equals K
      • Container With Most Water
      • Missing Number
      • Roman to Integer
      • First Missing Positive
      • Unique Integers That Sum Up To 0
      • Integer to Roman
      • Flatten
    • String
      • Check if two strings are permutation of each other
      • String Compression
      • Palindrome Permutation
      • Determine if a string has all Unique Characters
      • One Away
      • Longest Substring Without Repeating Characters
      • Valid Palindrome
      • Valid Palindrome II
      • Backspace String Compare
      • First Unique Character in a String
      • Is Subsequence
      • URLify a given string
      • String has same characters at same position
      • Number of Ways to Split a String
      • Check whether two Strings are anagram of each other
      • Print last `n` lines of a big file or big string.
      • Multiply Strings
    • Matrix
      • Search a 2D Matrix
      • Search a 2D Matrix II
      • Rotate Matrix
      • Spiral Matrix
      • Set Matrix Zeroes
    • Bit Manipulation
      • Sum of Two Integers
      • Reverse Number
      • Reverse Number II
      • Binary Bits Count
      • Binary Bits Count II
    • Stack
      • Valid Parentheses
      • Balance or not expression
      • Decode String
    • Tree
      • Binary Tree Inorder Traversal
      • Binary Tree Preorder Traversal
      • Binary Tree Postorder Traversal
      • Binary Tree Level Order Traversal
      • Binary Tree Return All Root-To-Leaf Paths
      • Binary Tree Height-Balanced
      • Valid Binary Search Tree
      • Binary Tree Sum of all left leaves.
    • Linked List
      • Linked List Delete Middle Node
      • Merge Sorted Linked List
      • Reverse Linked List
      • Remove Duplicates from Sorted List
      • Remove Duplicates from Unsorted List
      • Linked List Cycle
    • Graph
      • The Number Of Islands
      • Number of Closed Islands
      • Max Area of Island
      • Rotting Oranges
      • Number of Provinces
      • Course Schedule
      • Surrounded Regions
      • Snakes and Ladders
      • Widest Path Without Trees
      • Knight Probability in Chessboard
      • Possible moves of knight
      • Check Knight Tour Configuration
      • Steps by Knight
      • Network Delay Time
    • Greedy
      • Best Time to Buy and Sell Stock
      • Best Time to Buy and Sell Stock II
      • Smallest Subset Array
      • Jump Game
    • Backtracking
      • Towers of Hanoi
      • Subsets
      • Combination Sum
      • Sudoku Solver
      • Word Search
    • Heap
      • Kth Largest Element in an Array
      • Top K Frequent Elements
    • Sorting
      • Order Colors String
    • Recursion
      • Number To Text
      • Divide Number
Powered by GitBook
On this page
  • Solutions
  • Steps
  • Steps
  1. Problems
  2. Linked List

Remove Duplicates from Unsorted List

Given the head of a unsorted linked list, delete all duplicates such that each element appears only once. Return the linked list as well.

Solutions

Approach 1 – Using hash table


Easy solution, use hash table to check duplicate item.

Steps

  1. iterate through the linked list and adding each element to a hash table.

  2. Whenwe discover a duplicate element, we remove the element and continue iterating.

  3. Return head node.

/**
 * Definition for singly-linked list.
 * public class ListNode {
 *     public int val;
 *     public ListNode next;
 *     public ListNode(int val=0, ListNode next=null) {
 *         this.val = val;
 *         this.next = next;
 *     }
 * }
 */
public class Solution {
    public ListNode DeleteDuplicates(ListNode head)
    {
        HashSet<int> set = new HashSet<int>();
        ListNode previous = null;
        if (head == null) return null;

        ListNode temp = head;
        while (temp != null)
        {
            if (set.Contains(temp.val))
            {
                previous.next = temp.next;
            }
            else
            {
                set.Add(temp.val);
                previous = temp;
            }


            temp = temp.next;
        }
        return previous;

    }
}

Time Complexity: O(n)

Auxiliary Space: O(n)

Approach 2 – No Buffer Allowed


lf we don't have a buffer, we can iterate with two pointers: current which iterates through the linked list, and runner which checks all subsequent nodes for duplicates.

Steps

  1. iterate through the linked list and adding each element to a hash table.

  2. Whenwe discover a duplicate element, we remove the element and continue iterating.

  3. Return head node.

/**
 * Definition for singly-linked list.
 * public class ListNode {
 *     public int val;
 *     public ListNode next;
 *     public ListNode(int val=0, ListNode next=null) {
 *         this.val = val;
 *         this.next = next;
 *     }
 * }
 */
public class Solution {
    public ListNode DeleteDuplicates(ListNode head)
    {
        ListNode current = head;
        while (current != null)
        {
            ListNode runner = current;
            while (runner.next != null)
            {
                if (current.val == runner.next.val)
                {
                    runner.next = runner.next.next;
                }
                else
                {
                    runner = runner.next;
                }

            }
            current = current.next;
        }
        return head;

    }
}

Time Complexity: O(n²)

Auxiliary Space: O(1)

PreviousRemove Duplicates from Sorted ListNextLinked List Cycle

Last updated 1 year ago