 What's going on, everybody? Welcome back to the Excel tutorial series. Today we're going to create an entire project in Excel. Now, if you've never done a complete project in Excel where you take the data, you clean it, and then you create an actual dashboard where people can click on things and filter things. This is going to be a really great learning opportunity as well as potentially, you know, a simple project that you can use for your portfolio where you can spice things up and go a little farther than what we're going to be doing in today's video. I will walk you through every single step of the way and hopefully we learn something together and without further ado, let's jump right into it. Let's jump on my screen and get started with the project. All right. So this is the data set that we're going to be working with. I will leave a link in the description to my GitHub where you can go and download it so you can be working with the exact same data set that I am using. Now, before we actually get into this data and start looking at it, I'm going to show you what the final dashboard is going to look like. We're going to create a few different types of visualizations, nothing too crazy. And then we'll create some filters as well. So we can kind of, you know, create some interactive filters with our data. So let's go right on over to our data set. Now, I'm going to hide this because we are not going to use that. But what I am going to do before we do anything is I'm going to create a dashboard and I'm going to create a pivot table. Oops. And I'm going to create a working sheet. So all these things have different uses and I'll explain that as we go along. So this is our data set. I'm going to copy this over to our working sheet. When I go into, you know, an Excel and I'm working on something I don't like to, you know, use just the one that I was using in case I messed something up and it saves over it or some issue. I like to create a working sheet and keep the raw data right over here. It just makes my life easier. I don't have to save it and then, you know, open up a different Excel to compare them. So we have our bike buyers. This is our working sheets. This is our raw data. This is the one we're actually working on today. So let's, um, let's start looking at it really quick and just kind of glance and see what data we're working with. And then we'll start cleaning it up, making it more useful for what we are going to be using it for. And then we'll start building out the dashboard. So right here, we have an ID. That should be a unique ID to each person. Uh, this is their marital status. So married or single. This is their gender, male, female, have their income, children, their education, their occupation, do they own a home, how many cars they own, how long their commute is, the region where they live, their age, and if they purchased a bike. And this column right here is extremely important. This is going to tell us whether they did or did not buy a bike. So we got their information. They're looking for a bike, but they either decided not to buy a bike or they did buy a bike. And we're going to be using that one a lot in this video. And so, um, you know, this is basically the data set that we're working with. Um, some of the demographics and information behind the person. So what we want to do when we are cleaning the data, before we do anything, uh, I like to see if there are any duplicates in here. Um, what we were going to do is come right up here. Uh, we can go to, uh, pop up, um, where is it right here? We got remove duplicates. So we're going to click on that. It selects every single one. Um, we just want to see if there's any useless, duplicated data that we do not need, uh, and the data is a header. So we're going to click, okay. All right. So we had a ton of duplicates in there, uh, for whatever reason. So yeah, we do have duplicates in there. So I'm glad we did that. Otherwise we'd have, uh, you know, not good data and we don't want that. Let's start right over here. Um, the ID, of course, we're not going to change. The marital status and gender are M's, S's, F's and M's. Um, this isn't inherently a bad thing to have it like this, but you know, we have to think about it from the perspective of someone who's going to be using this dashboard. Do they know what M and S is? Do they know what M, uh, and F is? And if they don't, it's better to just spell it out for the most part. Um, so let's just do that. So we're going to click on the column B, we're going to hit control H. That's going to bring up our find and replace. Now there's an M in both of these columns and there's different things. One is married and one means male. So what we're going to do is we're going to search by columns. Um, and we'll have match case. I don't think that's going to change anything, but that just means an exact match. Uh, and we're going to do M equals and we're going to replace it with married. And we'll replace all. Awesome. And then we do S is single. This one is super easy. We're going to do the exact same thing right here. So column C, I'm going to hit control H we'll do still has by column. So we'll do M is male. We'll replace all of those and F is female and replace all of those. That's great. Uh, you know, the next column right here is income. And in this, in this previous video, I talked about how I don't typically like it in this format and that's true. Um, if you're doing calculations on it or any other thing, it can mess it up. Sometimes having the dollar sign or it being currency, we're not really going to mess with it too much right now. Um, what we can do is just kind of make sure all of its currency. Um, we'll just go like that to make it a little simpler, but we're not going to change it to like a numeric. Um, we will use this in the visualization. We'll see how it looks. And if we need to, we'll come back and change it. If not, we'll keep it how it is. Um, so that's all we're going to do to that one. Uh, the children, those look good. We have education, partial college, partial high school. This looks fine to me. Um, if there's any spelling errors or anything like that, of course, we need to clean that up. It doesn't look like there is occupation, skilled manual manual. Okay. Those should be separate with a homeowner should just be yes or no. All right. We have cars one, two, three, four. Good night. Who owns four cars? Um, and then we have the commute distance. Uh, and you know, there's nothing terrible about this. It's giving you ranges, um, which can be a good thing. I say let's keep it for now, but I have a feeling when we get further and we start using individualization, we may want to change this. So let's just hold off for now. Um, but if needed, we will come back to this and we'll change this. Um, and then we have our region and that looks totally fine. And we have our age. Now when you're using ages, typically you have some type of like age brackets or age range. And you do that because there are so many ages in here, right? It's 25 all the way down to 89. And if you're using that on some type of visualization, it could just get really messy. And so you'll create kind of, you know, just brackets around these so that you can kind of condense it and make it a little bit easier to understand. So let's do that and just create a new column. And then we can use that for our dashboard. So let's go right up here. We're just going to create a new column. Um, we'll call this age brackets. And what we can do is we can use an if statement to kind of say if it's older than or less than and kind of give them these ranges. Um, that's one way to do it. And that's the way we're going to do it right now. So let's go up here. And what we want to do is we want to say, is going to, we're going to say equals, we're going to do if, and we're going to close that parentheses. Now, what we're going to say is if this, I'll go right back up here. If this is less than, so we're going to do this 31 and we're going to say comma, so if they are less than 31, what do we want to call them? What do we want their, their, you know, name to be? We'll call them adolescent. Oops, that's not how you spell adolescent, adolescent. Um, and then if they're not, what we're going to do is we're going to say it's invalid. Okay. And let's just see if this one works first. Uh, right. It's not working at all. Um, okay. So basically what we did was, um, incorrect. We did it backward. Uh, we want to do, I said, uh, L two is greater than 31. No, we want to do like this. So let's do that now. All right. And it should pull up where if they're under the age of 31, so if they're 30 or below is basically what it's saying. So if they're 31, they'll be invalid. But if they're 30 or below, it's adolescent. So it is working properly. Um, and let's see what it, see what it says. Perfect. So this one is working and now what we want to do is we actually want to build on this and make it, uh, kind of like a nested if statement. If you've ever, um, heard of that or done that before. So this is our first if statement. And this is going to be, this is invalid. This is our value if false statement. This whole statement is going to become our value if false for a different if statement. Um, so let me write it out and hopefully that'll, uh, make sense. We're going to say if we do open parentheses and we're going to do it like this. And let's just get rid of this for a second. All right. Uh, what did I do? And let me do. Give me a second. Okay. We have our if, let me just write that out again. We have our if there we go. So now what we're going to do is we're going to write basically the next part of it. So we're going to say if that L two is, and we're going to do this time, we're going to do greater than or equal to 31. So now it's going to include that 31. So right here, we did anything less than 31. So it's 30 and below, this one is going to be 31 and above. So we're going to say these people are middle age. And if not, then it's going to go to this if statement. And then we need to close that, I believe. So now let's try this. All right. Fantastic. Now, if everybody should be in one of these areas, right, everyone should either be an adolescent or middle age, because basically all we're saying is, is if they're older than 31 or 30 or below. That's all these two statements do. So we have, you know, our next group. Now we can add and go even further into this. And now we can use this entire thing as the, um, what was it called the value if false section. So that's what we're going to do. We're going to do one more. So we're going to have three different categories. So we're going to say if and do, uh, an open parentheses. And we're going to say if, well, actually, let's do it. Um, let's not do it to this one. Let's do it to this top one. Just easier. Uh, so we're going to say if open parentheses, we're going to say L2. And this time we're going to say anybody over the age of 50. Uh, or we can do 55, let's do 55. So do 55 and we're going to call them old. And we'll do comma. This is the value if false statement and we need to close up parentheses. So let's try this. Anybody over the age of 55 should have old. Um, you know, maybe we'll do 54. So anybody who is 55 is considered old. I think that's fair. I think that's fair guys. Oops, I should have done. I should have done that to this one. Let me get out of this and we'll do 54. Uh, my dad is 55. That's why I'm doing it like this. This is for you dad. Uh, cause he should be in this old category to be fair. So now we have adolescent, adolescent, middle age and old. These are three categories. So we can now have these buckets, these different groups of ages. And it's much more usable than these individual ages. Um, and so we will be using this in our, in our dashboard for sure. Now our next one is the purchased bike. Uh, and we're not going to do anything with that. So, uh, you know, that is, that is that one. And you know, there wasn't a ton to clean up here. We removed some duplicates. Um, I don't know why it says that. What did I do? Married, married. What does this mean? It didn't mean I died right then. Did I mess this up guys? Oh, when I did the M and the S, uh, replacement in there, it replaced it with married and single. It's supposed to say marital status. Oops. Thanks for catching that guys. Thanks for catching that. I hope that's how you spell marital. Uh, we'll see. So, uh, we are going to keep it just like this. Now, what we are going to note now, what we are going to do is build pivot tables with this data. So we had our raw data, we have our working sheets, and now we want to create pivot tables and pivot tables is how you actually help build your dashboards to help build your visualizations. So we're going to go right here, we're going to hit, whoops, get rid of that. We're going to go right here. We're going to insert and we're going to say pivot table and it's going to ask us what range. So we're going to go back to the working sheets and we'll just click here and hit control a. This is going to select all of our data for us. So it's really easy and we're going to hit. Okay. And so now we have all of our, uh, pivot down, I don't need to pull it off. That was way too far. And now we have all of our pivot table information over here. And so that should make it really easy to, you know, actually build out. So what we're going to do is start selecting what columns and what data we actually want to work with. So the first one that we were going to build out is a dashboard that is basically looking at the average income of somebody who either bought or did not buy a bike. So we need in this one, we're going to need their income. That's definitely going to be a value right here. Um, but we want to break it out by male and female. So let's look at their gender. I'm going to pull that down into the rows. So, um, this is basically a sum and no, let's look at, uh, let's make this an average. I just went to the, um, I clicked right here. I went to the value field settings and we're just going to do an average. All right. And then we are going to make these, um, and as you can see, there's four decimal points, um, we'll keep it as is right now, but we may need to go back and change something. And then we're going to look at if they purchased a bike or not. And we're going to put that right here. So we can see that, uh, right here for the people who did not buy a bike, the females, their, their average salary was 53,000. The average salary for the average salary for males was 56,000. For yes, the ones who did buy a bike, the average salary was 55 for female and 60 for male. So the people who had a little bit more money or buying bikes, and you can also see that, uh, the men are making more money in this dataset just overall in general. Um, so let's make the visualization really quick, but you know, I don't know, I'm not a huge fan of these decimal points and maybe we can just change that in the visualization. We'll see. Um, oops, that's not what I meant to do. Um, let's do that. So what we are going to do is we're going to click into here and click insert. And we're going to go to these recommended charts and it's going to bring up basically every single type that we would want. Um, and we can just click in here and see which one looks good. Uh, oh yeah, I love those three D ones. Those are my favorite. You guys know that, uh, let's click, let's use this one right here. Pretty simple. Um, whoops, let's pull this right over here. And as is, it looks pretty good. Um, you know, it shows male, female, we have the average or the incomes right here, whether they did or did not purchase it. Um, and so at a glance, it's pretty easy to see. Let's see if there's anything, um, you know, if you want to change up style wise, go for it. I'm just going to keep it as is. Um, but let's see if there's anything we need to add, right? Do we want to add these access titles? Uh, one of the most parts I, I tend to do that. Um, it makes it pretty easy to see. So we can go in here and we can just click it like this and we'll say income and we'll say we'll do gender. That's what that is. And let's go back in here. Do we want to add a chart title? We definitely want to add a chart title. Uh, for most of these, we'll add a chart title for sure. So we'll say average income or purchase. Um, I don't know if that's 100% right, but we'll, we'll, we'll use it. Uh, if we need to change it to be, you know, by gender or something, we can, but, um, for now, let's see, do we want to add data labels? Uh, definitely not. Uh, a data table. Um, we can do this. It may make it a little easier to read. I will say that again, these numbers are just, these decimal points are really throwing me off. Let's go see if, um, we can change it in here. Uh, let's go to see if we can just make these numbers. Okay. And, um, we can keep it like that, or we can even do something like this at commas. Yeah, I'm going to keep it just like this. I think this just looks the best. Um, again, I'm, I'm getting adding commas here. I'm changing the, um, decimals place right here. It just makes it look a little nicer, a little cleaner. Um, so let's keep this exactly how it is. Um, we can always change things if we want to, uh, if we want to come back to it. So we created our pivot table and then we created our visualization. Basically exactly what we're going to do for all of these. Cause again, all of these need, um, you know, all of these need pivot tables in order to create the visualization. So let's, um, get out of here. We're going to scroll down and we're going to create our next pivot table. And once we get done with all of the pivot tables that we need, uh, all the visualizations that we need, then we will, um, we will start. So we're going to do control a, we're going to do okay. And basically do the exact same thing that we did. Um, this time we're going to look at the distance. So for this one, I wanted to see, you know, I try to, you know, I created this already. I've already done this entire project through, but I haven't really talked about why or what we're going to look at for this one. You know, we're looking at is their income, does it change whether they bought or didn't buy one? Um, so if they said yes, you know, is there a reason are they making more money is, you know, our price points are the customers. Did they make more money? So you should cater to them or not. Uh, that's a good question. Uh, another thing is, you know, we sell bikes or this person sells bikes. So commuting distance definitely makes a difference. Or, you know, does the person who is buying a bike live one mile away from where they work or 20 miles away. Uh, this will help us determine this next visualization will help us determine, you know, who is doing that or who's buying it. So what we're going to do is we are going to look at the, um, that one that we were looking at earlier, the commute distance. So we're going to bring that right over here. So we have these, you know, one mile, 10 mile, 1.2, et cetera. Now we are going to, uh, again, we're going to look at if they purchased a bike, that's really important. And let's make that the column as well. So now what we have is a count of these nos and yeses, whether they did or did not buy a bike. Um, one of the issues that I already see and we'll, I'm going to visualize it and then I'll show you that this 10 miles, you know, it's right next to the 0.1. So it's not an order. Um, and that could be, that could be an issue. Um, so we may have to revise that somehow to put it at the very bottom. Cause we can either do ascending or descending, uh, either when I don't think it's going to work. So we may have to work through that in just a second. Um, don't know if I did that in my plan for that. Um, yeah. So it has this big dip. Um, yeah. So let's, let's create it. Um, that's okay. We're going to figure this one out together. Cause I honestly, um, I didn't plan for this one. So, okay, we have 0.1 miles. That's exactly where it needs to be the one, the two, the five. That's exactly where it needs to be. This 10 miles is not. And let's see if I change that 10, 10 plus miles to 10 miles plus. Let's see if that'll put it down here. Cause I don't know if it's looking at, I don't know if it's reading it weird. Um, but let's go into this working sheet and let's go right here. I'm going to do control H and we'll do, oops, not this one. Um, 10 miles plus. Let's get that in there. And we're going to do 10, uh, miles plus. I don't know if that's actually going to work. Um, we will see. So let's go back to the pivot table. Let's re go to the data. Let's refresh. Uh, no, it didn't, it didn't change it. Um, okay. So let's think about this. Maybe if we change it to like a letter, it might change down here. So start it with, uh, miles. That could work. Um, let's try it. Okay. Sorry. Selected. Let's do the 10 plus miles. Okay. So let's do, um, ma, uh, more than 10 miles and we'll replace all. Get rid of this. Let's go to the pivot and refresh. All right. Okay. So it's not perfect, but it works. Um, and for what we're doing, I think we'll keep it how it is. So we have our second one. Uh, and, you know, there are different ways you can kind of change this one. Um, you know, in the last one, we did a ton of different stuff. We can do, um, just do commute distance. And we can say, what do we want to say on this one? What is this? Oh, this is the count. Um, could we have to keep this one? Um, no, there we go. I'm just going to do, um, just one and say commute distance and let's add a title. Chart title. We can make this one, um, let's say distance per customer. Uh, that's not a hundred percent true because it's nowhere. Yes. Um, that's, that's the important part of this. It's distance, um, average distance, uh, let's see. We'll just say customer commute. All right. And we'll keep it just like that. All right. Perfect. I don't think, um, let me see. I don't think there's anything else we need to add on that one. All right. Now let's go right down here. We're going to create our very last one. Uh, we only have three. So, you know, sometimes you'll have a ton. Sometimes you'll have like one on each sheet and you'll create multiple sheets, but, um, do control a, um, now we have our thing. Now this one, we're going to be looking at these age brackets that we were looking at that we created, um, something that I do, honestly, a lot is, is kind of bracket things and into groups like this. And you know, for this, I'm just kind of made them up, but, um, you know, it's good to know how to do this because I promise you this one happens a lot or I use this one a ton. And then we just want to look at who purchased a bike. Uh, so the same thing as we did before. So like purchase a bike, kind of the purchase, um, you know, pretty easy. So we just have the count of either no or yes for these age ranges. Um, and let's go to the inserts. We'll go to recommendation. Um, I personally like a good line for this one. Um, so let's, this is already interesting. If we do something like this, it's nice. See this one versus this, it just adds a dot. Well, it looks nice. We'll keep that one. Um, so just really quick at a glance, really interesting people under the age of 30 are not buying that many bikes. Um, age 30 to 54, uh, 31 to 54, buying a ton of bikes. Uh, they are, they buy more bikes or look at bikes more than anybody. Really interesting. Um, but we'll make the dashboard a little bit. Um, let's make these chart titles. We'll do. We're, oops, the horizontal was called this age bracket. Um, and then we'll add a chart title. Um, again, you can add some extra stuff if you want to. Um, but you don't need to, uh, none of this other stuff we really need. I'm just kind of looking at the stuff we do need. Or do want. Uh, so what do we want to call this one? It's called a customer age brackets. Um, and it's not perfect, but we'll keep it as is for comparison. Um, let me see if I can copy, um, or use this, um, real quick, instead of the age, uh, brackets, I'm going to get rid of this and use the age. And then let's use, um, let's insert recommendation. We use a line and we use this. So this compared to this, just think of it like if a customer or consumer or not a customer, uh, if somebody you're working with is trying to use this dashboard to understand this dashboard, this is going to be just, it's going to, I don't know, it might melt their brain. It just makes no sense. It makes sense. It's just all over the place. It's really hard to make sense of this. It really is. I mean, you can kind of see a pattern going up around like the mid thirties and then it trends downward, but it's hard to see. Um, it really is. So doing these, um, these brackets really helps and you can even add, you know, adolescents, um, you know, zero to 30 underneath it. And in fact, we may want to do that. Um, why not? Why not? Let's do that. Oh, whoops. Um, so why don't, why don't we do that? Why don't we go back? I'm just going to, I'm doing this on the fly. Why don't we go back? Uh, what am I doing? Whoops. And this is all calculated, but let's do adolescent zero to 30. Let's do middle aged 31 through 54 and then old 55 plus. Let's see if this breaks anything. I hope it doesn't. Um, and we'll go back to our pivot table. Let's refresh the data. Uh, okay. It did mess with stuff. Okay. Nevermind. Guys, that was a terrible idea. Don't do that. Um, perfect. Oh, let's get rid of that. That was a terrible idea. Don't do that. I'm glad we tested it out though. I like, I like to see if it was going to work. No, it messed with the, um, the order of things. Um, I, I intentionally named them adolescent middle age and all because it's, it, it makes sense for the visualization. Um, but you know, if I change something and it messes with it, I'm not going to mess with it. It was just an idea on the fly. Guys, come on. All right. So let's start building out our dashboard. Now, um, when we're building our dashboard, what I personally like to do is to have this pivot table sheet and then I will copy them over and later we'll hide these other sheets, um, and I'll explain that a little bit, but I like to have this, this one for us. So we're going to copy this. So I just click on it, hit control C. We're going to paste it right over here. Uh, let's just make them small for now. That's, oh gosh. No, let's not do that. Oh, these look terrible. Okay. Anyways, um, let's copy this one over. Oops. Okay. What did I just do? Oh, I didn't copy this one. Whoops. It's not copying. Okay. I'm going to go copy, hit paste. Fantastic. Oops. Guys, look away. This is, this is tough to watch. This is tough for me to watch. I'm the one doing it and it's tough for me to watch. All right. Let's go to this last one. I'm going to try it again. All right. It worked this time. So now we have, um, our three visualizations. This is perfect, but now we actually want to create a dashboard. Now, how do you do that? How do you make it look nice? Um, and then we're going to add some, you know, filters and stuff like that. How do we make it look nice? Um, what happened here? What changed? What do we do? Oh my goodness gracious. All right. Let's copy this. Let's paste this. Let's get rid of this. I don't even know how that happened. I've never seen that before. That was wild. Uh, Excel is trying to destroy my whole video. I mean, I'm doing this for you, Excel. Good night. Okay. No problem at all. What we're going to do and how you make this at least look nice. Um, first off, we can get rid of these grid lines pretty easily. And I recommend when you do that, when you make a dashboard, just makes it look cleaner and makes it look like an actual dashboard. Um, let's go to view and grid lines. So we can get rid of these grid lines. It just makes it look nicer. Um, we're going to make, you know, we can choose any color here. I'm just going to get choose a color. I like this. And let's, we're, we're basically creating like a header, right? If you're using like Tableau or something, um, we're going to merge and center. So it takes every single cell that we have highlighted creates into one. Let's call this, um, bike sales. Uh, I have, I think I called it bike sales dashboard. Let's just call it that. Um, you know, see what happens. Let's get that. Let's make it white and make it much larger than it is. Okay. Okay. Um, sure, let's do that. It doesn't look bad. Um, what is it doing? There we go. Uh, let's break that center. Perfect. Um, it's not perfect, but we're going to use it. All right. So now we kind of want to organize these and, you know, everybody has their different way of doing it. Uh, I'm just going to start building it out myself and just see how it looks. Uh, and then we'll go from there. I like this one there. Um, we can put this one. I, this one's a kind of a longer one. So I'll probably put it at the bottom and see how it looks. Um, but we'll put this one right here. Try to line it up. Geez. Let's, let's zoom in a little bit. Let's try to line this up. See what it looks like to extend it to the end. That doesn't look too bad. Uh, needs to move up just a hair. Uh, and I'll show you how to kind of align these in a second, but, um, that looks not bad and we'll kind of try to align these as well. Let me zoom out and extend this the length of this just to make it look nice. Um, you know, now what you can do and, you know, this is something that's pretty simple as you can get both of these and we're going to shape format and we can just align these is really nice to align, especially if like the top, um, and maybe like the left to right, but like, we're going to align these to the top and they just kind of align themselves on the very top. Now these look much better. This one is a larger dashboard or a larger visualization. So I'm going to keep it how it is. Um, and I'm going to keep this one how it is. So it is going to be a little bit smaller, as you can tell. And then we'll have this one. Um, and I'm going to do that. Um, I, this is going to bother me if I don't align these. So let me do this, shape format, align to the right. And it's not exactly what I want it to happen because, geez, what am I doing? That's not exactly what I want it to happen. I actually wanted this one to align this one to align with this one. It did the opposite. Um, so let me just scoot this back. All right. Visually it looks fine, but that's how you do it. If you want to do it. Um, I, I, if you have multiple of them like this, you can make it look bad. So we have our dashboards. This is already looking really good. I like how this looks. Colors are coordinated. It, we have a kind of a theme throughout, um, and it looks nice. I actually, I actually kind of want to change this one, um, to, um, let's see. Maybe if I did like that, it'd look nicer than all of them. Yeah, this does look nicer. Um, it doesn't change much either. Guys, I'm, should I do it? All right, we're going for it. We're changing the design on the fly. Should I do it for all of them? Let's see. It doesn't fit. Doesn't fit. Um, all right, guys, just ignore what I'm doing. Uh, don't do any of this. I'm just messing around at this point. So this is really great to have. It really is. And what we want to do is there are other elements. There are other things that people would like to feel to filter by and be able to look at, but it's not in this visualization. Um, to be more specific, one field that's could be really interesting is married versus single or single people buying more or, um, married people buying more, you know, it'd be nice to filter on it. So we're going to click on, uh, any of these actually, and we're going to go up to pivot chart analyze and we'll click insert slicer. Now we can choose which ones we want to be able to filter on all at the same time or one at a time. I'm just going to do the first one by itself and then I'll show you how to do other ones. Um, but this one is the marital status. So this is the married single, the one we were just looking at, and we can drag this right over here a little bit. All right. And we don't need all that space. I'm going to go all the way up now while we're doing this, um, it only because we selected this, uh, this visualization, it only is working on that one right now. We of course wanted to apply to all of them is not hard to do. All we're going to do is we're going to click on here. We're going to make sure we're clicking on this. We're going to go up to slicer and hit report connections. Um, and if you remember, we have this, um, this pivot table that we're working with, um, and this is where all of our pivots are coming from. So we're going to actually apply it to all of them. This is our sheet, um, and this is the name of the pivot table. Now, again, we created that fourth one. We're not using it, but we're going to apply it to all of them. So now when we click on it, it's going to apply to all of them. So at a quick glance, let's see what single people are doing. Um, interesting, interesting. Um, you know, when I'm looking at the, just these numbers right here, married people, these individuals are making a lot more like eight, um, sometimes eight to like 10,000 more on average, uh, than their single counterpart. Um, you know, again, that's a rough estimate, but it's, it's interesting. So now what we can do is we're going to create more of these. So we're going to go to, uh, pivot chart analyze. We're going to go to slicer. Now we already did marital status, but what if we want to look at things like, uh, region and maybe something like their education. So let's bring up both of those and look now, two of them come up. So let's add the region right here, bring that in just a little bit. See if we can match it, nailed it. All right. Now we're going to put that up. We'll bring this one down just like this, bring it over. See if I can match it again. Come on. Nay, almost nailed it. I don't know if I nailed it, but it's close. All right. Kind of bring this up a little bit, bring this up. And we have to do the exact same thing that we did with this one. Cause right now, again, it only applies to that one, um, chart. So what we want to do is we're going to go to slicer report connections, add it to all of them. Okay. Do the same thing with education or connections, but it being better. Boom. We are looking good. And now, uh, let's get rid of all of them. This is just going to be everybody. So now we can slice and dice and choose what we want. We want to look at people who have a bachelor's degree, who live in Europe and are single. And this is the information that we have on those people. So now we can narrow it down by certain demographics even further and look at this key information. So we may not, you know, look at counts and averages of these things, but we're able to filter on them. Uh, and that's really great to know. So bachelor's degrees on average are making 60s, 70,000. Um, let's look at, um, let's look at graduate degrees. Okay. A little more. Um, but you know, again, I'm just looking at random stuff. Um, but you can mess around with this, take a look at some stuff. Um, this to me, I want to make this color darker. I feel like it'd look nicer darker. There we go. Oh yeah. That's way better. This to me is, it's a good dashboard, right? You have key information that you're looking at, nice visualizations. It's color coordinated. You have these slices on the side. Um, to me, this is a fantastic, just simple dashboard. And there are so many other things that you can do with this data and you can make it unique and you can add your own spin on it. And I highly recommend that you do that. Push yourself, go past what we just did today and add your own stuff and use this. And then you can add this to your portfolio website and show this off and show people that you know how to use Excel, which is a fantastic thing to know how to use and show off. So with that being said, I hope that this project was helpful. I hope they learned something along the way. I know I did. Um, I was learning things as we were going and I hope that you didn't mind that I took some detours along the way, um, for your amusement as well as my learning. Uh, so with that being said, thank you so much for joining me. I really appreciate it. I hope you have a good day and goodbye.