I watched some 4-5 videos for this problem , but this is hands down the most easiest and intuitive way of solving. Thanks a ton
@Chirayu19 Жыл бұрын
Initially what I did is finding the element through binary search and then iterating left and right to find leftmost and rightmost. But now I realized in worst case that would be O(N). Thanks a ton for this video!
@mr.victory.8 ай бұрын
same
@nataliagrigoryeva66156 ай бұрын
As always, such a great explanation! I have a small suggestion for a slight efficiency boost: if the target is not in the array, we could run the binary search once and set right to -1 if left is -1, without running the binary search a second time.
@aryanyadav39262 жыл бұрын
Using leftBias boolean variable was very clever.
@aviralarpan73502 жыл бұрын
Lol
@MsSkip603 жыл бұрын
Great thanks! Tried tuning a little bit further and start searching after we found initial match but lots of edge cases in that case tbh
@nishanttanwar993 жыл бұрын
Great Explanation, I found the video using the link given in the leetcode post. This solution is so intuitive and is much better than the solution provided with the Leetcode problem. Keep up the good work.
@yalebass Жыл бұрын
it makes total sense to use binary search to find the left and rightmost instances if the target, I don’t know why I suddenly let my code return to O(n). Thanks for the vid!
@healing10002 жыл бұрын
Thank you. This is better than all leetcode discuss solutions. I don't even think I will forget this one
@appcolab2 жыл бұрын
Wow!! Man, I love this. I was just coming across some complicated solutions but this 🔥, thank you so much!
@anandhu50823 жыл бұрын
after r=m-1 and l=m+1, won't it be better if we return if the values in this new position != target? (To stop the search to left(or right) if we already reached left(or right) end)
@ShivangiSingh-wc3gk2 жыл бұрын
The binary search updates were very intutive thank you
@vaibhavdesai162 жыл бұрын
I was used similar approach but I used binary search exit condition as (nums[mid] == target && nums[mid -1] != target) similarly for right bias it will nums[mid+1] != target. This one is much cleaner
@vikassharma-ky1dv7 ай бұрын
We can optimise it further by finding first index , if not found we need not find second Index
@yfh70242 жыл бұрын
Hi, I have a question: my code looks almost the same to you expect my mid is m = l + (r - l) //2, when it executed test case: [2,2] 3, I got exceed time limit. but when I changed it to m = (l + r)//2, my code was accepted.
@yunaliu59462 жыл бұрын
Best solution that I have ever seen
@HR-pz7ts Жыл бұрын
My first approach was binary search and it unfortunately didn't worked and had to switch to linear search and it worked just fine after a few tries with using few conditions and Boolean. And for some reason it was better than 100% java submissions for time complexity.
@qazyip2 жыл бұрын
If I use a two pointer method, left at index 0 and right at end of length, traverse each until both meets the target and return left, right. Would this be o(n)?
@Lambyyy2 жыл бұрын
Yes, O(n)
@jennielieu3312 Жыл бұрын
Do we need to define the leftBias function?
@anshumansharma67583 жыл бұрын
You explain very well. Thanks for working hard on these explanations
@eshabaweja Жыл бұрын
solved it myself; here to compare and improve :)
@CasualyinAir3 жыл бұрын
Thanks! Very clean approach. I like your explanation too, very concise.
@chenlee79342 жыл бұрын
This is the best explanation i watched, thank u.
@ChanChan-pg4wu2 жыл бұрын
Great Explanation! Thanks for your smart and hard work.
@atg8784 ай бұрын
great of the greatest 🙌🙌
@ltxlouis39182 жыл бұрын
Thank you! Great explanation
@danielbzhang3280 Жыл бұрын
Here's my solution: def searchRange(self, nums: List[int], target: int) -> List[int]: leftpos, rightpos = -1, -1 l, r = 0, len(nums)-1 while l = 0 and nums[mid-1] == target: mid -= 1 leftpos = mid while mid+1 target: r = mid - 1 else: l = mid + 1 return [leftpos, rightpos]
@pragateesh5545 Жыл бұрын
smart
@haruhipoulain8953 Жыл бұрын
It's O(n), when we have the test case like (8, 8, 8, 8, 8), target 8.
@glen66382 жыл бұрын
Nice , it’s easy to understand.👍
@sivaganesh44892 жыл бұрын
awesome explanation
@danishshaikh61515 ай бұрын
If we just add This will reduce 1 extra logN is the target is not present if left == -1: return [-1, -1]
@basic-2-advance5 ай бұрын
Bringing the Algorithms 101 class Solution: def searchRange(self, nums: List[int], target: int) -> List[int]: def binary_search_leftmost(A,T): L = 0 R = len(A) while L < R: m = floor((L + R) / 2) if A[m] < T: L = m + 1 else: R = m return L def binary_search_rightmost(A,T): L = 0 R = len(A) while L < R: m = floor((L + R) / 2) if A[m] > T: R = m else: L = m + 1 return R - 1 l = binary_search_leftmost(nums,target) r = binary_search_rightmost(nums,target) return [l,r] if target in nums else [-1,-1]
@eamonmahon66222 жыл бұрын
Why can't the helper function be nested and just have leftBias as the input argument?
@sanjeeeeev3 жыл бұрын
Best Explaination EVER 🔥
@edwardteach25 ай бұрын
U a binary search God
@satyakidas4835 Жыл бұрын
Hi I am getting an error SyntaxError: 'return' outside function can you please suggest what to do?
@arindammandal15132 жыл бұрын
Always love ur explanation bro!!!
@sensei17812 жыл бұрын
Since its sorted cant you just iterate once you find either the left or right target index?
@myroncarvalho48722 жыл бұрын
time complexity would be O(n) in that case the moment you start iterating. coz in worst case you can have an array with all elements as target.
@samCoder3 жыл бұрын
Had I watched your video before my interview, I would have cleared the interview :(
@SaulLee663 жыл бұрын
Could we do it in one while loop?
@ShashwataSaha-wb8qd Жыл бұрын
How's it Log(N) everywhere it's showing as Log(N) TC. But no, it's O(Log(N)) before it enters in the last else block, as it enters the last else block it will iteratively reset the binary search for about log(N) times. So the time complexity should be O(log(N)*log(N)). Open to suggestions.
@haruhipoulain8953 Жыл бұрын
In the last loop we have some l and r index, so we have some range like r - l + 1 to check. And after that it not get bigger, after one operation we always get to check (r - l + 1) / 2 range. So it's log(n) because we always divide range by 2
@LazyCoder207 ай бұрын
Its easy to do it using lower bound and upper bound - 1.
@akshayskumar2427 Жыл бұрын
what is the use of leftbias?
@AdityaBhongade7 ай бұрын
Respect, sir!
@Vivekkumar-zc7mz7 ай бұрын
we use upper bound and lower bound for this
@jnayehsirine62225 ай бұрын
ur channel is a safe place to me haha
@今天比昨天厲害3 жыл бұрын
You are amazing!
@abhinav_mittal Жыл бұрын
can some one tell me why can't i use this:- class Solution: def searchRange(self, nums: List[int], target: int) -> List[int]: for i in nums: if target not in nums or len(nums)==0: return [-1, -1] elif target in nums: return [nums.index(target), len(nums) - 1 - nums[::-1].index(target)] And also this doesn't satisfy the Case 3:- Input: nums = [], target = 0 Output: [-1,-1] Please tell me why .....
@RichItUp5 ай бұрын
Because the time complexity will be O(n) in the worst case. If all the elements are target.
@5_tejabvs818 Жыл бұрын
isn't the time complexity O(log(n^2))
@igorf2437 ай бұрын
how is it medium?
@henrydi8002 жыл бұрын
why need to update the left and right pointers when finding the target variable
@haruhipoulain8953 Жыл бұрын
Because we need to search most left and most right el
@nagendrabommireddi8437 Жыл бұрын
thanks boss
@xinniu31452 жыл бұрын
Thanks this is so clear!
@nodirbekhbudi12083 жыл бұрын
How to run this in jupyter notebook
@jhonrobaon16693 жыл бұрын
Code is good but for worst case, the complexity would be O(n) which is not acceptable
@denniskang67683 жыл бұрын
can you pls explain why it's O(n) in worst case?
@yuanfeng4843 Жыл бұрын
class Solution: def searchRange(self, nums: List[int], target: int) -> List[int]: def binSearch(leftBias): l, r, i = 0, len(nums)-1, -1 while l nums[mid]: l = mid + 1 elif target < nums[mid]: r = mid - 1 else: i = mid if leftBias: r = mid - 1 else: l = mid + 1 return i return [binSearch(True), binSearch(False)]
@yashsolanki3665 Жыл бұрын
Nice
@krishgusain39592 жыл бұрын
got it
@__Y1a2s3h4__2 жыл бұрын
This code doesn't works for me
@gxyxy101212 күн бұрын
m= l + (r-l)/2
@eugene6070 Жыл бұрын
hello my fellow sharpenarians
@nathamuni94352 жыл бұрын
hay
@sniff46433 жыл бұрын
video request!: leetcode.com/problems/jump-game/ the DP solution is quadratic time. but the greedy one is linear?! could you help explain how the greedy works lol
@NeetCode3 жыл бұрын
Yeah, I like that problem, I'm gonna try to do it soon, thank you for the request!
@shubham24402 жыл бұрын
93% Faster - 64 ms and 61% better memory usage class Solution(object): def searchRange(self, nums, target): l=0 h=len(nums)-1 loc = ['p']*2 if len(nums)==0: return [-1,-1] if len(nums)==1 and target==nums[0]: return [0,0] if len(nums)==1 and target!=nums[0]: return [-1,-1] while l
@ARkhan-xw8ud4 ай бұрын
why i = -1
@raymonddelacruz979013 күн бұрын
if the target can't be found in the array the expected result would be -1 that's why i = -1
@lostmeme98622 жыл бұрын
I cheated and used floats.
@piyushbansal97163 жыл бұрын
lol i came for the edge cases and they are not there whats the point on teaching the simple binary search 😂😂
@arunr22653 жыл бұрын
can you provide one edge case
@aleksproger_il Жыл бұрын
My solution: public class Solution { public int[] SearchRange(int[] nums, int target) { int[] res = {-1, -1}; if(nums.Length == 0) return res; int l = 0; int r = nums.Length - 1; while(l