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Hi, everyone.

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So in the last videos, we discussed how we can use our own to make some priority.

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Now in this video.

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We will discuss how we can use our inbuilt minimum priority queue.

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So we will start using our built Menom prior to.

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Q So let's directly jump into court and let's see this index for creating our inbuilt minimum priority.

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Q So if I remember this is our old code, so this is actually maximum and if you in the output, if

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you will run this program, then what will be our output.

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So you can see the size of six and the topmost elements from six to seven.

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And then when we are getting each element one at a time, so the output is going to be in descending

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order first, the largest element will come, then the smaller one, then the smaller, smaller, smaller

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and the smallest.

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So our output is coming out and decreasing order because we are using maximum.

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Now let's see how we can create our minimum.

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So let's change its name to be good to.

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So now let's see this index, Susan, index is quite similar.

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So proud of you, I want to create a priority queue of integers, so integers, then you have to write.

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Retrophin digits, and then you have to rate greater.

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Indigence and.

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This is your beginning.

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So this is this index for creating minimum I know this index of minimum prior to kill is really weird,

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but we will not go into much detail.

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So we will just we will just remember this line that we have to use.

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We have to write the digits and then we have great, great advantages.

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So I will provide you note that what is the meaning of character?

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So this is the way for creating minimum.

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Now the name is Piku and I change its name to Picado, so I am pushing in priority queue.

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So the size is still six, but the topmost element is the smallest element and the smallest element

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is now one.

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So will come out first and I am wiping out the elements from the minimum priority queue Bittu.

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So this time our elements will come out and sorted.

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Amended, correct.

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So now let's try to test our called.

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So you can see this is the size is going to be some other topmost element is the smallest element and

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other elements are coming out and sorted because we are using minimum.

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So the minimum element will come out first, then the next element will come out first.

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And in this way, at the last, we have the largest element.

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So now we know how to create minimum.

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So let's just solve one more question.

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So if you remember the last question, so our last question was to find the smallest element.

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So the last question we did was to find the smallest element.

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Now, can we use minimum priority queue to find out the smallest elements?

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So what I will do, the logic is very simple.

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I will push every element inside the minimum priority queue.

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So these are my total elements.

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So create a minimum priority queue.

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And push every single element inside your priority queue, so five, then six, then nine, then 12,

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then three, then 13 and then to.

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What do I want, I want the smallest elements.

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So what I will do, I will call pop function.

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Three times.

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Basically, top and bottom, top end pub function combination, so find out the top most elements of

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the topmost element is to sort of come out first and then pop the element of pop to then.

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So I have to call three times now, the second time, Bob, the smallest element.

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So three will come out first.

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And Bob.

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So he's getting Bob now.

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I will pop out five because five with the smallest element and five will be here.

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And then I have to do three times.

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So I will stop.

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And this is my game.

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Smallest element.

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Now if you will use medium priority queue, then your time complexities, same as and Logan just like

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this one, because ultimately what you are doing the size of your minimum priority is going to be when

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at first you have to insert any elements.

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So for inserting an elements, the time complexity will become analogue and then you will run the loop

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times.

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Basically you will call the append function.

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So this will become Kellogg.

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And so this will be the time complexity, if you will, use the minimum priority for solving this question.

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So let's take one more example.

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So what I'm saying is.

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So let's take this one example, it five 12, 10 zero one six nine, and the value of it is actually

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for.

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So that you can understand how we can use minimum priority code was all above question.

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So my Ed is very simple.

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This is eight, then five then.

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Well, then let's say 10, then let's say zero.

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Then let's say one.

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Then let's say six and nine.

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And what is the value of K?

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So the value of Gaisford.

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Correct.

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Now this is already.

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So what I will do, I will iterate over this.

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This is my minimum priority queue.

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I will agree or disagree and I will push every element inside my priority queue.

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Correct.

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So all these elements will be pushed inside my priority.

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So let's change the name.

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So this is my priority.

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You correct.

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Now, what I will do, I will.

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Run the loop four times and I will call the function top and then I will call the function pop.

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So this is priority queue, so the minimum element will come out first.

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So zero is the minimum element.

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So top pop zero.

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Now, when is the minimum element?

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Pop and pop?

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What is the minimum now, five, stop and pop, what is the minimum element now?

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I think it is six sort of benchtop and now I will stop.

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So this is my answer.

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Zero one five six.

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Correct, so I can use medium priority queue and the complexities of first, we have to insert all the

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elements into the priority queue.

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So time, complexity, there are an element.

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So when loop so and login and then we have to pop out key elements so key and the to produce login so

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caillaux and login plus login.

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Correct.

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And the space is going to be big off and because the protocol will contain N elements.

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So obviously the maximum practical approach for solving this question was the best approach.

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And this approach is not even better than discarding one, so starting approach was better than this

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one, starting was better.

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So but we are not discussing about time, complexity, and we are just trying to use in particular,

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we're just trying to learn how we can use inbuilt protection.

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So let's write the code.

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So this was the call for the smallest element.

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Now, what I want to do, I will create a minimum priority.

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So let's just come in and out everything.

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OK, so let's get one more function.

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So wait, so let's namer to.

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So guess my list again, it will take it is and but it will take the size and it will take a very bulky.

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Then they have to do so, we have to create a minimum priority, given the syntax, basically you have

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to remember this index.

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So proud of indigence, then you have to read.

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Vector of integers, then you have to rate greater of integers and please, there's no need to go in

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detail, you just remember that this is how we create I impractical.

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So this is a minimum heap, correct.

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Now, the approach is very simple.

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Push every element inside your main priority queue.

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So I equals zero.

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Equals zero, i.e. less than a plus plus they're going to push every single element, every single element

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into my priority given to Alfy, I am pushing every element and then I will pop out key elements.

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So pop key elements and these key elements.

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Will be the smallest elements because this is minimum hip.

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So I have to run the loop times, so.

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I equals one I less than what equals gay and I placeless.

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Scout, Bacolod Top.

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And Bechard artpop.

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And we know the output is going out before this area is five Trenta, but the output will come out unsorted,

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so the output will be two, three and five, correct?

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So you can see.

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Earlier, I was using Makhzoumi, so my output was just the reverse of this five, three and two, but

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here I am using minimum heap, so the output is two, three and five.

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So two, three and five at the three smallest element present in this given area.

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So that's how we can use minimum hyp.

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So I think I have discussed the time, complexity, all sorts of decisions and log in and this is key

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log and correct.

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Now, this question was to find.

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So this question was to find the smallest element, so let's say the maximum priority queue was giving

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me the best time in space complexity.

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Now, if the question is to find the just element.

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If the question is to find the killer element, so it is very obvious that the minimum help will give

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me the maximum, the minimum, it will give me the best time and space complexity.

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I am repeating myself in this question.

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We have to find the smallest element.

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So that's why the employer was giving me the best approach, because I will maintain the size.

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The size will be key.

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If the question is this one, then I will lose my employer.

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You and I will maintain the size of an employer to Kyuki.

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Now in this question also, so, for example, the question is just if we want to use Mixin prior to

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you, you can definitely use what you will do.

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You will push every single element.

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So you will push every single element inside your priority queue.

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So time, complexity and Logan and then what you have to do so we won't get so I will pop out key elements.

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So these key elements will be the largest element.

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So Kellogg, Kellogg and.

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Simple so in this question, if you will choose to make simpler, to do everything will just become

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a perceived.

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So simpler to dismiss time, complexity and I mean practical will give me and longer time complexity.

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Now, there is one more way to insert elements into your priority queue, so first tell me, how much

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is the time complexity for this call?

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What I am doing so I am creating a minimum priority queue.

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And then I am reading over the air and I am inserting elements into my priority given by one element

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of time, complexities of time, complexities and Logan.

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Just remember, this time, complexities and Logan, now there is one more way to insert elements into

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your priority queue.

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So instead of writing, so let's copy this one now, I just need the first line.

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So the above code was inserting the elements time, complexity was analog and.

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Now, if you will insert the element in this, we.

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Acoma, Apison.

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So now the time complexities go off and.

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Maritime complex, it is big often, so let's test our record.

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So, see, our report is correct, two, three and five.

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Our goal is working fine.

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So if you will insert the elements in this way, one by one, I'm inserting the elements one by one.

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So there are time complexities going to be and Logan.

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So what is the difference between this method and this matter?

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The workers say they are just inserting the elements inside your priority queue, but what is the difference?

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So in this approach, what we are doing, we are taking elements one by one.

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Elements are coming one by one.

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But in this way, what we did, we provided just Holyday Edwards, we provided all the elements at once,

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so that's why the time complexity decreases.

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So here the time complexities Magoffin and the time, complexities and Log-in similarly.

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If so, if you want to insert vector, for example, instead of ETTY, if we're using vectors of what

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we will write, we will write vector dot begin.

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Basically, we have to give the first and the last address to begin and end.

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Instead of writing a plans and just like in these sorting function, sort my person or you can write

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Saat we begin Victor not we begin my view.

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So there is no need to go into much detail by the time complexities is often probably.

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I will just create one video to explain to you by the time complexities big.

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And so for now you can just remember that if you look at it prior to you using this matter, perhaps

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the whole idea was then the time complexity for inserting the elements as big often and then wasted

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time complexity.

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If the elements are coming one by one, then the then your time complexities and log-in.

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So just remember this time complexity.

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I will just probably create one more video explaining why it is so.

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OK, so this is how you can use minimum priority.

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You just remember this index.

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Everything will work fine.

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So what is this trained teacher?

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So what I will do, I will upload some notes and you can at those notes, but frankly telling you there's

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no need to go into detail why this is so.

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Just remember the syntax and do the work.

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Nothing much.

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So I will see you in the next one by.