 What's going on everybody? Welcome back to the Power BI Tutorial series. Today, we're gonna be taking a look at bins and lists. Now bins and lists are really useful because they allow you to group things together to analyze and visualize them easier. So in this tutorial, I'll show you how to create your bins and lists and then we'll create some visualizations to show you how it can be helpful. So without further ado, let's jump on my screen and get started with the tutorial. All right, so before we get started, I wanted to let you know you can go and download the data that we're gonna be using in this tutorial. In the description below is on my GitHub. So we are gonna be looking at bins and lists today. And for this, we're gonna be going over here to this Apocalypse Sales. And let's open up our data right over here. And we wanna look at Apocalypse Sales really quickly. I feel like more people would know what a bin is. So we'll kind of start with a list, just go a little bit backwards than we normally would. I'm gonna use this customer, or we're gonna use this customer column right here for a list really quickly. And you can do that in two ways. You can come up here and you can right click on the customer and go to new group. Or you can come over here under the field section on the far right and go to customer, right click and click new group. So let's click on that now. And right now is only giving us the list type. It's not giving us bins because bins have to be numeric. So we really can't do that at the moment. So we're gonna call those just customer groups, or we'll actually call it list so it's easier to recognize when we create it. And so all we're gonna do is we're gonna basically group these, but it's gonna be called a list. And so what we're gonna do is we're gonna select and we're gonna select and we're gonna say group and click on this group button. And then it creates this Alex the Analyst Apocalypse Preppers and this prep for anything prepping store. So it kind of named it for us. But if we double click on it, then we can rename this and we can call this the best prepping stores. And then we have these last two and we can click on one and then click control and click on the other one so we get both of them. And then we can click group and we can call this and we'll double click and we'll call this the worst prepping stores. And then that's it. And that's all we have to do. And what we're then going to do, and if you want to undo this and you want to switch it up and do whatever, you can click on group, but we're not gonna do that. We're gonna click okay. And here is the column that it created and it basically tells us what list we put it in. If it's Uncle Joe's prep shop, that's in the worst prepping stores list. And if it's the Alex the Analyst Apocalypse Preppers, that is in the best prepping stores. So it's kind of like an if statement. You could even create a calculated column, do it on this customer, create an if statement. This is just a lot faster and a lot easier than doing that, but it basically would do the exact same thing. Now you can use lists as well on things like numeric. So let's say we have order ID and we'll go to new group and it's gonna auto go to bin because typically that's what you'll use, but you can do list as well. And let's say, you know, we wanna say, we wanna call these like, we'll group these and call these the first, we'll call this the first customers or the first orders, because we're looking at order IDs. Look at the first orders. And then we will go back here. We're going on the left side, we're gonna click. Oops, we're gonna go back to the top. We're gonna hit shift, group all of these and we'll say the latest orders. And you absolutely can do this. Again, this is kind of like an if statement, right? So you're saying if it falls between this range and this range, then it's called the first orders. And if it's between this range and this other range, it's the latest orders. Again, it's just a much simpler version of an if statement. And so you don't have to write it all out. You can just have this user interface to kind of do it for you and it's really, really useful. So now let's talk about bins and by far the easiest way to demonstrate this and I'll show you one other way, but by far the easiest way to show this is by using age. And so for absolutely no reason whatsoever, these customer IDs who are right here and this customer information, they decided to give us some of their buyer information who are actually buying their products on their website or in their store. They just decided to give it to us as well as some simple demographic information. I don't know why. But what we're gonna use bins for is grouping these age brackets. So you might be interested in saying, well, I wanna know if my core population who are buying my products are within a certain range and you don't wanna look at every single age because then it just, you know, on your visualizations it's not gonna look right. You wanna kind of group them, make it easier to visualize. So what we're gonna do is we're gonna go through here and we're gonna basically go by tens. So 10, 20, 30, 40, 50, 60 and see what age bracket these people fall in. So we're gonna go to age, we're gonna right click and we're gonna say new group and we're gonna go to bin and we'll leave it as the default age bins. And you can do two things. You can do the size of the bins, which splits it by this number right here or you can go based on the number of bins. So if you only wanna do five different bins, it'll calculate that for you and it'll say, okay, if you only want five bins, you're gonna have to do it at 12.2. If you want 10 bins, it could be 6.1. But it is completely up to you on how you want to do that. You can do the size and we'll just say every 10, which is what we're gonna do. Or you can go through and then you can create how many bins you actually want. So let's go ahead and click okay and it's gonna create those bins for us. So if somebody is 78, they're gonna be in the 70s bin. If somebody is 41, they'll be in the 40 bin. If somebody is 29, they'll be in the 20 bin and so on and so forth. So when we go to visualize this, we don't have 71, 72, 73, 74, have a lot more things on our visualization. It'll just be the 70 or it'll just be the 20. Now we can also use bins on dates as well. So let's go back to apocalypse sales. We have this date purchase. So we can create a bin for this as well. So let's go to date purchased. Let's go new group. Now you can also create a list and that's totally fine if you would like to do that. And it would look kind of like this where you can go through and you can select it and you can say, okay, this group, all these dates, you can group those and say, this is gonna be January. And you can do that and that's totally okay. But for this one, we're gonna do bins and I think it's a little bit easier to do bins because what we can do is go right here and we can specify if we want seconds, minutes, hours, days, months or years. And so for the data that we have, it goes January, February and March. So we're gonna do months and we're gonna say the bin size is gonna be one month. So each month should have its own bin. So it'll be three bins total. So we're gonna select okay. And as you can see on this right side, we have January of 2022. Now it correlates to the January over here. Then it goes down to February and then it goes down to March. And then when we visualize this, we don't have to do the hierarchy stuff that we do in here where we filter it down to months. We can just use this right here and that will be our months column. So now let's go over to our visualizations and we'll see how this looks really quickly. We're not gonna look at all of them but we will take a look at a few of them. So the first one that we can look at is age. So let's look at the buyer ID and then we'll do age as well. And so let's spread this out. And we can see our distribution of our buyers. So it looks like we have very few, who are in the 10 range, thank goodness. And we can even put the age right under here under the age bins and we have this, now we kind of have this drill down. And so if we go right here and we drill down right there, this will actually give us the breakdown. So this is what it would have kind of looked like, our visualization would have looked like if we had just kept it the age because now we're drilling down into the age. And so it looks like we have one 18 year old and maybe a 20 year old as well. Let's go back up. Yeah, so it looks like we only have one buyer ID. Yeah, so there's only one 18 year old. So of legal age to start buying all these prepping equipment and probably buying online and stuff like that, which makes sense, right? So this gives you kind of a quick breakdown in the bins rather than doing it the alternative way. So now let's take a look at the customer list as well as the unit sold. And it looks like the best prepping store is actually performing much worse surprisingly than the worst prepping store. And so I hope this gave you a really good idea of how to use bins and lists within Power BI. Thank you so much for watching. If you liked this video, be sure to like and subscribe and check out all my other videos on Power BI. I'll see you in the next video.