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Preface
- FAQ
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Part I - Basics
- Basics Data Structure
- Basics Sorting
- Basics Algorithm
- Basics Misc
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Part II - Coding
- String
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Integer Array
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Remove Element
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Zero Sum Subarray
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Subarray Sum K
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Subarray Sum Closest
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Recover Rotated Sorted Array
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Product of Array Exclude Itself
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Partition Array
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First Missing Positive
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2 Sum
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3 Sum
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3 Sum Closest
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Remove Duplicates from Sorted Array
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Remove Duplicates from Sorted Array II
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Merge Sorted Array
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Merge Sorted Array II
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Median
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Partition Array by Odd and Even
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Kth Largest Element
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Remove Element
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Binary Search
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First Position of Target
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Search Insert Position
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Search for a Range
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First Bad Version
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Search a 2D Matrix
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Search a 2D Matrix II
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Find Peak Element
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Search in Rotated Sorted Array
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Search in Rotated Sorted Array II
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Find Minimum in Rotated Sorted Array
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Find Minimum in Rotated Sorted Array II
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Median of two Sorted Arrays
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Sqrt x
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Wood Cut
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First Position of Target
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Math and Bit Manipulation
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Single Number
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Single Number II
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Single Number III
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O1 Check Power of 2
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Convert Integer A to Integer B
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Factorial Trailing Zeroes
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Unique Binary Search Trees
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Update Bits
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Fast Power
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Hash Function
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Happy Number
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Count 1 in Binary
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Fibonacci
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A plus B Problem
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Print Numbers by Recursion
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Majority Number
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Majority Number II
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Majority Number III
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Digit Counts
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Ugly Number
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Plus One
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Palindrome Number
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Task Scheduler
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Single Number
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Linked List
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Remove Duplicates from Sorted List
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Remove Duplicates from Sorted List II
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Remove Duplicates from Unsorted List
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Partition List
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Add Two Numbers
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Two Lists Sum Advanced
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Remove Nth Node From End of List
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Linked List Cycle
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Linked List Cycle II
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Reverse Linked List
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Reverse Linked List II
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Merge Two Sorted Lists
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Merge k Sorted Lists
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Reorder List
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Copy List with Random Pointer
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Sort List
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Insertion Sort List
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Palindrome Linked List
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LRU Cache
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Rotate List
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Swap Nodes in Pairs
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Remove Linked List Elements
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Remove Duplicates from Sorted List
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Binary Tree
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Binary Tree Preorder Traversal
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Binary Tree Inorder Traversal
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Binary Tree Postorder Traversal
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Binary Tree Level Order Traversal
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Binary Tree Level Order Traversal II
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Maximum Depth of Binary Tree
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Balanced Binary Tree
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Binary Tree Maximum Path Sum
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Lowest Common Ancestor
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Invert Binary Tree
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Diameter of a Binary Tree
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Construct Binary Tree from Preorder and Inorder Traversal
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Construct Binary Tree from Inorder and Postorder Traversal
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Subtree
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Binary Tree Zigzag Level Order Traversal
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Binary Tree Serialization
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Binary Tree Preorder Traversal
- Binary Search Tree
- Exhaustive Search
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Dynamic Programming
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Triangle
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Backpack
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Backpack II
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Minimum Path Sum
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Unique Paths
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Unique Paths II
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Climbing Stairs
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Jump Game
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Word Break
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Longest Increasing Subsequence
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Palindrome Partitioning II
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Longest Common Subsequence
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Edit Distance
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Jump Game II
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Best Time to Buy and Sell Stock
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Best Time to Buy and Sell Stock II
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Best Time to Buy and Sell Stock III
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Best Time to Buy and Sell Stock IV
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Distinct Subsequences
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Interleaving String
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Maximum Subarray
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Maximum Subarray II
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Longest Increasing Continuous subsequence
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Longest Increasing Continuous subsequence II
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Maximal Square
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Triangle
- Graph
- Data Structure
- Big Data
- Problem Misc
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Part III - Contest
- Google APAC
- Microsoft
- Appendix I Interview and Resume
-
Tags
Remove Duplicates from Sorted Array II
Question
- leetcode: Remove Duplicates from Sorted Array II | LeetCode OJ
- lintcode: (101) Remove Duplicates from Sorted Array II
Follow up for "Remove Duplicates":
What if duplicates are allowed at most twice?
For example,
Given sorted array A = [1,1,1,2,2,3],
Your function should return length = 5, and A is now [1,1,2,2,3].
Example
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题解
在上题基础上加了限制条件元素最多可重复出现两次。因此可以在原题的基础上添加一变量跟踪元素重复出现的次数,小于指定值时执行赋值操作。但是需要注意的是重复出现次数这种方法比较复杂,谢谢 @meishenme 提供的简洁方法,核心思想仍然是两根指针,只不过此时新索引自增的条件是当前遍历的数组值和『新索引』或者『新索引-1』两者之一不同。occurence
的初始值(从1开始,而不是0)和reset的时机。
C++
class Solution {
public:
/**
* @param A: a list of integers
* @return : return an integer
*/
int removeDuplicates(vector<int> &nums) {
if (nums.size() <= 2) return nums.size();
int len = nums.size();
int newIndex = 1;
for (int i = 2; i < len; ++i) {
if (nums[i] != nums[newIndex] || nums[i] != nums[newIndex - 1]) {
++newIndex;
nums[newIndex] = nums[i];
}
}
return newIndex + 1;
}
};
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Java
public class Solution {
/**
* @param A: a array of integers
* @return : return an integer
*/
public int removeDuplicates(int[] nums) {
if (nums == null) return -1;
if (nums.length <= 2) return nums.length;
int newIndex = 1;
for (int i = 2; i < nums.length; i++) {
if (nums[i] != nums[newIndex] || nums[i] != nums[newIndex - 1]) {
newIndex++;
nums[newIndex] = nums[i];
}
}
return newIndex + 1;
}
}
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源码分析
遍历数组时 i 从2开始,newIndex 初始化为1便于分析。
复杂度分析
时间复杂度 , 空间复杂度 .