Understanding Data Structures and Algorithms

For most people, studying data structures and algorithms is not the most exciting part of programming. And trust me, this is exactly the feeling that I used to have when I first started learning about data structures and algorithms. To me, they just seemed so boring and I just couldn't quite understand why they're even important. And this seemed like something that I just sort of have to learn to get my foot through the door. And after that, I can just forget about them and focus on what I'm actually excited about, like coding Tinder bots. But now that I've actually properly learned about these topics and taken the time to actually understand not only what they are but why they're important, I've actually completely changed my mind. I think data structures and algorithms is one of the most beautiful parts of programming and computer science. And in this video I want to give you a glimpse of this beauty by giving you literally the dumbest most simple explanation of what data structures are. to give you sort of an intuitive understanding that you can then take into your actual study of each particular data structure so you can have this sort of framework in your mind going into it and hopefully hopefully you may even start to appreciate the beauty that implementing data structures can actually have and believe me i remember exactly what it was like to not understand anything about data structures this video is completely language agnostic so whichever programming language you've learned in the past you can watch this video and then at the end And as always, I will give you the exact resources that I use in a step-by-step way to go from this conceptual high level understanding into mastering all of these topics. I'm really passionate about data structures and algorithms. So if you enjoyed this video, there will be a very similar video coming on algorithms as well. So if you do enjoy this video, leave a like down below because how many people like this video will then sort of tell me whether I should make it or not. Okay, so what are data structures? I had an extremely. high level, all a data structure is, is a way of organizing data. So whenever you're writing a program, the purpose why computers exist in the first place is that we have some data, which can be like numbers or maybe it's a string, and then we have something that we want to do with that data to produce some useful result. It turns out that it really matters how we actually organize data in a computer's memory. And I know that right now, None of this makes any sense. And that is why I have organized a couple of very specific examples, which will allow you to actually understand it again in the dumbest way possible in a way that even a literal dumbass like me could understand how this works. But first, let's just briefly talk about why this idea of organizing data is actually so important to the point where if you want to get a job, studying data structures and algorithms is literally the most important thing that you need to know. You're good at data structures. and algorithms, you will be good at writing programs in a logical way, in a way that makes sense in a way that is efficient and what companies want to see is that you have that fundamental knowledge and those principles that you can apply in their production code to make the code really good and therefore so that you as the programmer are worth the money that the company is spending on you. So a data structure is a way of organizing data in the computer's memory. The way the computer's memory works in again a really dumb sort of simplified way you have these memory blocks which are called like memory registers. All these registers hold some kind of value. Maybe this is a two, this is a five, this is a seven. And whenever you're writing a program, you're probably not just doing something with one piece of data like this two here. Often you'll have something like a collection of data that are sort of related to each other in some way. Maybe it's a list of numbers, like a list of transactions that you want to add together or something like that. So it makes sense to actually organize this data close to each other in the computer's memory so that it's easy for you to access all. these different pieces of data rather than having to define separate variables like a equals two or b equals five you can just define one variable or one data structure called a list and this is the first data structure that we learned the most basic one and then you put all of these numbers into this one variable so then in the future if you want to access the middle element of this list you can just go list one from the computer's perspective when all of these variables are stored close together to each other accessing them together and maybe looping over them or something is a lot easier. This is sort of the computer equivalent of let's say like when I'm making these YouTube videos right there's multiple pieces of gear that I always sort of need and so whenever I want to start filming a video it makes sense if I've sort of placed all my camera gear in the same part of the room. So all I have to do is go to that part of the room grab the gear and start filming and storing values in something like a list is just a computer equivalent of this same principle. So let's talk about a limitation that a very simple data structure like a list could have. have. The way lists or arrays are used usually define in a programming language is there is certain amount of memory in this case we've just allocated three registers of memory to our list here. But what happens if we now want to add a fourth element to the list? Well, you might say that, well, that's easy. We just sort of add it here. But what if this register in the memory was already taken up by a different piece of data? Maybe we already had a string like hello in here. Now we put the eight on top of it. So this hello gets replaced. And maybe we had a different part of the program where we were using that piece of string. And now instead of hello, it's certainly an eight and just everything crashes, right? So the way Liz Lists are usually actually defined under the hood in the language is that if you add an element to a list, it will actually take this list and move it to a completely different part of the memory and then allocate more memory to it. Even if you don't understand anything about low level programming, you might see that this is sort of very inefficient. If you know that you'll be constantly adding data to a list every time moving into a different location in the memory can become very slow. So that is why you can see that actually, if we know that the thing we want to do with our data is. to keep adding stuff to it. And we know that in the future, we'll be adding a lot of stuff to it. It actually doesn't make sense to use a list and there might be a better way to organize that data again for this purpose that we have here. And in particular, for something like this, we might use something called a linked list. And what a linked list is, instead of storing your items just sequentially after each other in the memory, what we're doing is we're defining this node structure. So we just have two places in memory where the first one is a piece of data, like I'll... two here and the next one is a pointer to a different node somewhere else in the memory. It doesn't matter where it is. Essentially this second item of this node will be pointing to the next element which will again just be a node and the way this actually works is that these memory registers are numbered in the computer's memory. Let's say this is a number five this number six and then somewhere randomly in the memory we have memory register I don't know like 102 and here as the second element of this first node. we just have the memory address where we know that the second element will be. And again for the next one we would have maybe a pointer to register 463 and this one will then know that okay the next element of our linked list will be in memory location 463. And again using our camera example here let's say I'm using all my camera gear in this part of the room here but now there's no space anymore. What I could do is include like a post-it note in that area to see that okay the next batch of my gear. is going to be in this area of my room. Maybe there's a note there that says, I don't know, under the bed or something so that I know where to go to find the next part of the gear. And this way you can essentially just keep increasing this chain of values or chain of camera gear almost indefinitely, as long as you actually have a space in your memory or space in your room. All you have to do is just know where the very last element of the list is. And then you just have to find an empty location anywhere in your memory and then add, you know, node into your linked list. And so you can see how we already with this very simple requirements we already sort of have a need for a slightly more complex data structure and from the programmers perspective we want to add something to the list you just call the linked list sort of a method that's defined inside of the data structure to append an element in the list and under the hood all of this stuff is happening all this sort of drama is happening but the programming doesn't even need to know anything about it. But crucially if the designer of this program hadn't designed this in the correct way it could be causing a problem like this and causing the whole hardware to essentially crash or explode or whatever horrible things would happen. But again obviously even the linked list also has downsides. Let's say what's really important in the specific application we're developing is for example accessing elements in the middle of the list like accessing this one right here. Now this specific operation is actually a lot easier to do in an array or a list like data structure we just call list one like this here whereas with a linked list we just sort of have to loop over the list until we we arrive at the item that we're looking for, which is a lot more expensive. So as you can see, again, which data structure we're using always depends on the specific thing we're trying to do and sort of the specific things that you can see the user of that program needing to do a lot of the time. And the way all of this, like the linked list, would be implemented in an actual programming language or Python is that you would do something like create a class called linked list. Then you would create a method inside that do all of this magic. And then there will be a client where all they would have to do is call call this append method and it would simply just do all this magic behind the scenes. And that is really the beauty of data structures. And I know that all the details of this might be a bit fuzzy for you. Again, the point of this video is not so that you can understand all these details. It's just to give you an idea of why different data structures even exist. If my sort of weird way of explaining data structures is making sense to you at all, I would appreciate it if you could tap the like button. Down below in the description. So let's now move on to a couple of slightly more complex examples to really drill this in and to make sure that you really understand what's going on here. But first a word from our sponsor. If you have a business or you're working on a project that requires e-signature, you want to make sure that your documents are signed securely, fast and in a legally binding way. So if that's you, You need to listen. The SignNow API is a powerful e-signature tool that allows you to embed e-signature on your website. It's free to test, fast to deploy, and will allow you to not worry about document approval cycles and instead focus your time on... growing your business. Developers particularly love SightNow's easy to use and detailed documentation with clear coding examples as well as great video tutorials on how to get started which makes implementing the API extremely easy in any programming language. The SignNow API is available through straightforward SDKs and allows you to complete entire document approval cycles from uploading documents to tracking signature progress. And not only that, the SignNow API makes sure that your apps keep running with 99.99% uptime and in accordance with all the required compliance and security requirements. So if that is something that sounds useful for your app, you are in luck because they currently have a unique offer on the market which gives you 250 legally binding e-signatures for free. free so if you don't want to miss out on that click the link down below in the description to create your free sandbox account and start building dynamic e-signature workflows today thank you for sign now for sponsoring this video and now back to the tutorial so in practice we obviously have a lot more even more complicated requirements for things we want to do with data let's say you're an airline and you want to sort of structure the data about all the people who have bought tickets to some flights. What makes sense for you is probably not just to group stuff together randomly in the computer's memory like for example in the order that they bought their tickets because what you probably really want to do is order them in some sort of priority where the people who have bought first class tickets are first so that when they want to do something with it they can see the first class passengers first and then the business class passengers and then the peasant economy passengers like me. So it would be very useful for these airline operators to have a data structure that would allow them to group. group data in a way like this. And it turns out this is a very common requirement in many different computer programs. And that is why a very common data structure that is used is something called a priority queue. Now for this, you would define essentially a linked list just like this, but essentially every time when you're adding something to the list, but the add method wouldn't just be doing this. It wouldn't just be adding it to the end of the list, but rather every time we're adding a person, it would do some sort of operations which automatically sort of orders the list in the way that the airline wants. So it It orders it in a priority order. So here, what we would probably have is instead of just a piece of data and the link to the next node in the list, we would have also a field for the priority class of the passengers. So we would have a node that looks something like this where there's three values. There's the actual person. Probably this would already be something like a dictionary with like their name and their birthday and the price they paid or whatever. We would just have a value that indicates that this is a business class passenger. And here again, we would have a pointer that would be something like this. So the memory address of the next person on the list. And then every time we're adding a person, we would have defined inside the data structures of app operations that automatically perhaps it calls a different function to reorder all the passengers in such a way that this passenger enters into the correct location of the list. So as you can see, a lot of the time, even though you might think about data structures as just about the structure, so where we put the data, a lot of the time, especially these more complex data structures are a lot more about the operations that we want to do with that data. That is really the other thing that you should keep in mind that when you're defining data structures is really not just the organization of the data, but also the operations that we define on that data. And again, the point here is that the airline operators or the person who's like going through the ticket doesn't need to know anything about any of this drama that's happening down there in the computer memory, because the programmer, the programmer who understands data structures has been able to program it in an intelligent way from. from the airline operators perspective, all of this is just happening like magic. When they add a new ticket into the pool of ticket holders, the list is automatically organized in the exact priority that they want. And that is again, the magic of data structures. And this whole principle is also something that we often refer to as abstraction. The most beautiful thing about computers and computer science is that there's like a million different levels of abstraction where at the very low level, you just have zeros and ones inside the computers or even lower than the transistor. where electricity is going through these logic gates, but you don't need to know about any of these because there are low-level programmers who have designed these higher level programming languages that allow us to do stuff with the low-level computer without understanding all the drama that's happening down below. Same thing here, when as a programmer, as a high level programmer, your most important task is to understand the language and to understand programming concepts like data structures in such a way that you can design programs so that the people who use these programs don't need to know anything about how they work. They can just use them, you just tell them, click this button, or run this function, and it will do exactly what they want. And in reality, the relationships with pieces of data and the things we want to do are even more complicated than this. For example, if you're organizing a webpage like like the way Google actually organizes their webpage. They have these like very complicated relationships with like all the different webpages. So they need structures to deal with it, again, for the purposes that they need the data for. And so at the end of the day, the reason why companies care about all of this, the reason why you need to know all of this as a programmer, it's like the equivalent of someone who organizes their room like a complete mess. No one wants to hire someone who doesn't know how to organize their work effectively and to do stuff in a- efficient way and so this is the analogy of the programmer who just does stuff in a way that maybe works but it's not the most efficient way to do it and for companies especially in these large enterprises where all these details really matter because they're dealing with like billions of pieces of data they want to hire programmers who can organize their code effectively and that is really what data structures are all about if you want to actually now learn these details obviously this video is not enough first of all i would recommend subscribing to this channel because again if enough of you like this video I want to make a similar video about the other side of these structures and algorithms, which is algorithms But really to learn all of this is not easy and to learn it effectively You need a good step by step plan and a path to make sure that you're learning Everything that you need to know in the most efficient way possible and for that I'll give it for you I mean this video where I talk about exactly that I describe exactly an exact step by step plan that you can take from a high Level overview into all the theoretical details if you want to master all of these topics and learn to pass coding interviews, you should absolutely watch this video right here.

And after that, I can just forget about them and focus on what I'm actually excited about, like coding Tinder bots. But now that I've actually properly learned about these topics and taken the time to actually understand not only what they are but why they're important, I've actually completely changed my mind. I think data structures and algorithms is one of the most beautiful parts of programming and computer science. And in this video I want to give you a glimpse of this beauty by giving you literally the dumbest most simple explanation of what data structures are. to give you sort of an intuitive understanding that you can then take into your actual study of each particular data structure so you can have this sort of framework in your mind going into it and hopefully hopefully you may even start to appreciate the beauty that implementing data structures can actually have and believe me i remember exactly what it was like to not understand anything about data structures this video is completely language agnostic so whichever programming language you've learned in the past you can watch this video and then at the end And as always, I will give you the exact resources that I use in a step-by-step way to go from this conceptual high level understanding into mastering all of these topics.

I'm really passionate about data structures and algorithms. So if you enjoyed this video, there will be a very similar video coming on algorithms as well. So if you do enjoy this video, leave a like down below because how many people like this video will then sort of tell me whether I should make it or not. Okay, so what are data structures? I had an extremely.

high level, all a data structure is, is a way of organizing data. So whenever you're writing a program, the purpose why computers exist in the first place is that we have some data, which can be like numbers or maybe it's a string, and then we have something that we want to do with that data to produce some useful result. It turns out that it really matters how we actually organize data in a computer's memory.

And I know that right now, None of this makes any sense. And that is why I have organized a couple of very specific examples, which will allow you to actually understand it again in the dumbest way possible in a way that even a literal dumbass like me could understand how this works. But first, let's just briefly talk about why this idea of organizing data is actually so important to the point where if you want to get a job, studying data structures and algorithms is literally the most important thing that you need to know.

You're good at data structures. and algorithms, you will be good at writing programs in a logical way, in a way that makes sense in a way that is efficient and what companies want to see is that you have that fundamental knowledge and those principles that you can apply in their production code to make the code really good and therefore so that you as the programmer are worth the money that the company is spending on you. So a data structure is a way of organizing data in the computer's memory. The way the computer's memory works in again a really dumb sort of simplified way you have these memory blocks which are called like memory registers.

All these registers hold some kind of value. Maybe this is a two, this is a five, this is a seven. And whenever you're writing a program, you're probably not just doing something with one piece of data like this two here. Often you'll have something like a collection of data that are sort of related to each other in some way. Maybe it's a list of numbers, like a list of transactions that you want to add together or something like that.

So it makes sense to actually organize this data close to each other in the computer's memory so that it's easy for you to access all. these different pieces of data rather than having to define separate variables like a equals two or b equals five you can just define one variable or one data structure called a list and this is the first data structure that we learned the most basic one and then you put all of these numbers into this one variable so then in the future if you want to access the middle element of this list you can just go list one from the computer's perspective when all of these variables are stored close together to each other accessing them together and maybe looping over them or something is a lot easier. This is sort of the computer equivalent of let's say like when I'm making these YouTube videos right there's multiple pieces of gear that I always sort of need and so whenever I want to start filming a video it makes sense if I've sort of placed all my camera gear in the same part of the room.

So all I have to do is go to that part of the room grab the gear and start filming and storing values in something like a list is just a computer equivalent of this same principle. So let's talk about a limitation that a very simple data structure like a list could have. have. The way lists or arrays are used usually define in a programming language is there is certain amount of memory in this case we've just allocated three registers of memory to our list here. But what happens if we now want to add a fourth element to the list?

Well, you might say that, well, that's easy. We just sort of add it here. But what if this register in the memory was already taken up by a different piece of data? Maybe we already had a string like hello in here. Now we put the eight on top of it.

So this hello gets replaced. And maybe we had a different part of the program where we were using that piece of string. And now instead of hello, it's certainly an eight and just everything crashes, right?

So the way Liz Lists are usually actually defined under the hood in the language is that if you add an element to a list, it will actually take this list and move it to a completely different part of the memory and then allocate more memory to it. Even if you don't understand anything about low level programming, you might see that this is sort of very inefficient. If you know that you'll be constantly adding data to a list every time moving into a different location in the memory can become very slow. So that is why you can see that actually, if we know that the thing we want to do with our data is. to keep adding stuff to it.

And we know that in the future, we'll be adding a lot of stuff to it. It actually doesn't make sense to use a list and there might be a better way to organize that data again for this purpose that we have here. And in particular, for something like this, we might use something called a linked list.

And what a linked list is, instead of storing your items just sequentially after each other in the memory, what we're doing is we're defining this node structure. So we just have two places in memory where the first one is a piece of data, like I'll... two here and the next one is a pointer to a different node somewhere else in the memory.

It doesn't matter where it is. Essentially this second item of this node will be pointing to the next element which will again just be a node and the way this actually works is that these memory registers are numbered in the computer's memory. Let's say this is a number five this number six and then somewhere randomly in the memory we have memory register I don't know like 102 and here as the second element of this first node.

we just have the memory address where we know that the second element will be. And again for the next one we would have maybe a pointer to register 463 and this one will then know that okay the next element of our linked list will be in memory location 463. And again using our camera example here let's say I'm using all my camera gear in this part of the room here but now there's no space anymore. What I could do is include like a post-it note in that area to see that okay the next batch of my gear. is going to be in this area of my room.

Maybe there's a note there that says, I don't know, under the bed or something so that I know where to go to find the next part of the gear. And this way you can essentially just keep increasing this chain of values or chain of camera gear almost indefinitely, as long as you actually have a space in your memory or space in your room. All you have to do is just know where the very last element of the list is. And then you just have to find an empty location anywhere in your memory and then add, you know, node into your linked list.

And so you can see how we already with this very simple requirements we already sort of have a need for a slightly more complex data structure and from the programmers perspective we want to add something to the list you just call the linked list sort of a method that's defined inside of the data structure to append an element in the list and under the hood all of this stuff is happening all this sort of drama is happening but the programming doesn't even need to know anything about it. But crucially if the designer of this program hadn't designed this in the correct way it could be causing a problem like this and causing the whole hardware to essentially crash or explode or whatever horrible things would happen. But again obviously even the linked list also has downsides. Let's say what's really important in the specific application we're developing is for example accessing elements in the middle of the list like accessing this one right here.

Now this specific operation is actually a lot easier to do in an array or a list like data structure we just call list one like this here whereas with a linked list we just sort of have to loop over the list until we we arrive at the item that we're looking for, which is a lot more expensive. So as you can see, again, which data structure we're using always depends on the specific thing we're trying to do and sort of the specific things that you can see the user of that program needing to do a lot of the time. And the way all of this, like the linked list, would be implemented in an actual programming language or Python is that you would do something like create a class called linked list.

Then you would create a method inside that do all of this magic. And then there will be a client where all they would have to do is call call this append method and it would simply just do all this magic behind the scenes. And that is really the beauty of data structures.

And I know that all the details of this might be a bit fuzzy for you. Again, the point of this video is not so that you can understand all these details. It's just to give you an idea of why different data structures even exist. If my sort of weird way of explaining data structures is making sense to you at all, I would appreciate it if you could tap the like button. Down below in the description.

So let's now move on to a couple of slightly more complex examples to really drill this in and to make sure that you really understand what's going on here. But first a word from our sponsor. If you have a business or you're working on a project that requires e-signature, you want to make sure that your documents are signed securely, fast and in a legally binding way.

So if that's you, You need to listen. The SignNow API is a powerful e-signature tool that allows you to embed e-signature on your website. It's free to test, fast to deploy, and will allow you to not worry about document approval cycles and instead focus your time on...

growing your business. Developers particularly love SightNow's easy to use and detailed documentation with clear coding examples as well as great video tutorials on how to get started which makes implementing the API extremely easy in any programming language. The SignNow API is available through straightforward SDKs and allows you to complete entire document approval cycles from uploading documents to tracking signature progress.

And not only that, the SignNow API makes sure that your apps keep running with 99.99% uptime and in accordance with all the required compliance and security requirements. So if that is something that sounds useful for your app, you are in luck because they currently have a unique offer on the market which gives you 250 legally binding e-signatures for free. free so if you don't want to miss out on that click the link down below in the description to create your free sandbox account and start building dynamic e-signature workflows today thank you for sign now for sponsoring this video and now back to the tutorial so in practice we obviously have a lot more even more complicated requirements for things we want to do with data let's say you're an airline and you want to sort of structure the data about all the people who have bought tickets to some flights.

What makes sense for you is probably not just to group stuff together randomly in the computer's memory like for example in the order that they bought their tickets because what you probably really want to do is order them in some sort of priority where the people who have bought first class tickets are first so that when they want to do something with it they can see the first class passengers first and then the business class passengers and then the peasant economy passengers like me. So it would be very useful for these airline operators to have a data structure that would allow them to group. group data in a way like this.

And it turns out this is a very common requirement in many different computer programs. And that is why a very common data structure that is used is something called a priority queue. Now for this, you would define essentially a linked list just like this, but essentially every time when you're adding something to the list, but the add method wouldn't just be doing this.

It wouldn't just be adding it to the end of the list, but rather every time we're adding a person, it would do some sort of operations which automatically sort of orders the list in the way that the airline wants. So it It orders it in a priority order. So here, what we would probably have is instead of just a piece of data and the link to the next node in the list, we would have also a field for the priority class of the passengers.

So we would have a node that looks something like this where there's three values. There's the actual person. Probably this would already be something like a dictionary with like their name and their birthday and the price they paid or whatever. We would just have a value that indicates that this is a business class passenger.

And here again, we would have a pointer that would be something like this. So the memory address of the next person on the list. And then every time we're adding a person, we would have defined inside the data structures of app operations that automatically perhaps it calls a different function to reorder all the passengers in such a way that this passenger enters into the correct location of the list.

So as you can see, a lot of the time, even though you might think about data structures as just about the structure, so where we put the data, a lot of the time, especially these more complex data structures are a lot more about the operations that we want to do with that data. That is really the other thing that you should keep in mind that when you're defining data structures is really not just the organization of the data, but also the operations that we define on that data. And again, the point here is that the airline operators or the person who's like going through the ticket doesn't need to know anything about any of this drama that's happening down there in the computer memory, because the programmer, the programmer who understands data structures has been able to program it in an intelligent way from.

from the airline operators perspective, all of this is just happening like magic. When they add a new ticket into the pool of ticket holders, the list is automatically organized in the exact priority that they want. And that is again, the magic of data structures.

And this whole principle is also something that we often refer to as abstraction. The most beautiful thing about computers and computer science is that there's like a million different levels of abstraction where at the very low level, you just have zeros and ones inside the computers or even lower than the transistor. where electricity is going through these logic gates, but you don't need to know about any of these because there are low-level programmers who have designed these higher level programming languages that allow us to do stuff with the low-level computer without understanding all the drama that's happening down below.

Same thing here, when as a programmer, as a high level programmer, your most important task is to understand the language and to understand programming concepts like data structures in such a way that you can design programs so that the people who use these programs don't need to know anything about how they work. They can just use them, you just tell them, click this button, or run this function, and it will do exactly what they want. And in reality, the relationships with pieces of data and the things we want to do are even more complicated than this.

For example, if you're organizing a webpage like like the way Google actually organizes their webpage. They have these like very complicated relationships with like all the different webpages. So they need structures to deal with it, again, for the purposes that they need the data for.

And so at the end of the day, the reason why companies care about all of this, the reason why you need to know all of this as a programmer, it's like the equivalent of someone who organizes their room like a complete mess. No one wants to hire someone who doesn't know how to organize their work effectively and to do stuff in a- efficient way and so this is the analogy of the programmer who just does stuff in a way that maybe works but it's not the most efficient way to do it and for companies especially in these large enterprises where all these details really matter because they're dealing with like billions of pieces of data they want to hire programmers who can organize their code effectively and that is really what data structures are all about if you want to actually now learn these details obviously this video is not enough first of all i would recommend subscribing to this channel because again if enough of you like this video I want to make a similar video about the other side of these structures and algorithms, which is algorithms But really to learn all of this is not easy and to learn it effectively You need a good step by step plan and a path to make sure that you're learning Everything that you need to know in the most efficient way possible and for that I'll give it for you I mean this video where I talk about exactly that I describe exactly an exact step by step plan that you can take from a high Level overview into all the theoretical details if you want to master all of these topics and learn to pass coding interviews, you should absolutely watch this video right here.

Transcript for:Understanding Data Structures and Algorithms

Transcript for:
Understanding Data Structures and Algorithms